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CALSCALE:GREGORIAN
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BEGIN:VEVENT
SUMMARY:Shiva Razavi (MIT)
DTSTART:20230627T150000Z
DTEND:20230627T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/1
DESCRIPTION:Title: Autocatalytic base editing for RNA-responsive translational control
\nby Shiva Razavi (MIT) as part of Seminar on Biological Control Systems\n
\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/1/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Enoch Yeung (UCSB)
DTSTART:20231024T150000Z
DTEND:20231024T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/2
DESCRIPTION:Title: Data-Driven State Criticality and Observability with Koopman Operator M
ethods in Biological Networks\nby Enoch Yeung (UCSB) as part of Semina
r on Biological Control Systems\n\n\nAbstract\nI will present two major re
sults to show the use of data-\ndriven Koopman methods to identify critica
l states and observable\nsubspaces to solve problems in synthetic biology.
In the first\, I\npresent the use of dynamic mode decomposition (DMD) to
model the\ntranscriptome-wide response of a root-isolate bacterium to a no
vel\nchemical compound. By solving an observability maximization problem\n
for the DMD model\, we find a panel of biomarkers that can act as\neffecti
ve biosensors for the compound\, even in field studies with the\nbacterium
. This study establishes a new precedent for reasoning about\nstate critic
ality and system observability\, even without prior\nknowledge of a networ
k model. Second\, I present new theoretical\nresults that show how Koopman
methods can be used to evaluate\ncriticality of states to optimize perfor
mance of a nonlinear system.\nHistorically\, this problem is solved using
either direct sensitivity\nanalysis on a known model or by generating loca
l function\ndistributions that span the nonlinear observable subspace of a
system.\nIn the absence of a known model\, I present a new Koopman-based
method\nfor estimating the observable subspace of a nonlinear system purel
y\nfrom data. Our results provide a route for data-driven discovery of\ncr
itical states that affect an output-based performance measure.\n\nBio:<
/b> Enoch Yeung is an Assistant Professor in the Department of Mechanical
Engineering at the University of California Santa Barbara. He is the di
rector of the Biological Control Laboratory\, which is an interdisciplinar
y laboratory that aims to bring together expertise in control theory\, syn
thetic biology\, and systems biology to develop new mechanisms for biologi
cal control and computing. Prior to his appointment at UCSB\, Enoch was
a Senior Research Scientist at the Pacific Northwest National Laboratory.
He holds a PhD in Control and Dynamical Systems from the California Insti
tute of Technology and is the recipient of the NSF CAREER award\, the Army
Young Investigator Program award\, and a Keck Foundation award.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/2/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Heidi Klumpe (Boston University)
DTSTART:20230926T150000Z
DTEND:20230926T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/3
DESCRIPTION:Title: Deep neural networks for predicting single cell responses and probabili
ty landscapes\nby Heidi Klumpe (Boston University) as part of Seminar
on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/3/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Stanislav Anastassov (ETH-Zürich)
DTSTART:20230829T150000Z
DTEND:20230829T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/4
DESCRIPTION:Title: A cybergenetic framework for engineering intein-mediated integral feedb
ack control systems\nby Stanislav Anastassov (ETH-Zürich) as part of
Seminar on Biological Control Systems\n\n\nAbstract\nThe ability of biolog
ical systems to tightly regulate targeted variables\, despite external and
internal disturbances\, is known as Robust Perfect Adaptation (RPA). Achi
eved frequently through biomolecular integral feedback controllers at the
cellular level\, RPA has important implications for biotechnology and its
various applications. In this study\, we identify inteins as a versatile c
lass of genetic components suitable for implementing these controllers and
present a systematic approach for their design. We develop a theoretical
foundation for screening intein-based RPA-achieving controllers and a simp
lified approach for modeling them. We then genetically engineer and test i
ntein-based controllers using commonly used transcription factors in mamma
lian cells and demonstrate their exceptional adaptation properties over a
wide dynamic range. The small size\, flexibility\, and applicability of in
teins across life forms allow us to create a diversity of genetic RPA-achi
eving integral feedback control systems that can be used in various applic
ations\, including metabolic engineering and cell-based therapy.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/4/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Guillaume Gines (CNRS/ESPCI Paris)
DTSTART:20230530T150000Z
DTEND:20230530T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/5
DESCRIPTION:Title: DNA-enzyme neural networks enabling nonlinear concentration profile cla
ssification\nby Guillaume Gines (CNRS/ESPCI Paris) as part of Seminar
on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/5/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Eszter Csibra (Imperial College)
DTSTART:20230328T150000Z
DTEND:20230328T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/6
DESCRIPTION:Title: Absolute protein quantification using fluorescence measurements with FP
CountR"\nby Eszter Csibra (Imperial College) as part of Seminar on Bio
logical Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/6/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Corentin Briat (ETH-Zurich)
DTSTART:20230228T160000Z
DTEND:20230228T170000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/7
DESCRIPTION:Title: Structural stability in integral rein control\nby Corentin Briat (E
TH-Zurich) as part of Seminar on Biological Control Systems\n\nAbstract: T
BA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/7/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Zibo Chen (Westlake University)
DTSTART:20230131T160000Z
DTEND:20230131T170000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/8
DESCRIPTION:Title: A synthetic protein-level neural networks in mammalian cells\nby Zi
bo Chen (Westlake University) as part of Seminar on Biological Control Sys
tems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/8/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Diego Oyarzun (University of Edinburgh)
DTSTART:20221025T150000Z
DTEND:20221025T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/9
DESCRIPTION:Title: Multiobjective optimization feedback control circuits for metabolic eng
ineering\nby Diego Oyarzun (University of Edinburgh) as part of Semina
r on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/9/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Fangzhou Xiao (Caltech)
DTSTART:20220927T150000Z
DTEND:20220927T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/10
DESCRIPTION:Title: Biocontrol of biomolecular systems: polyhedral constraints on binding'
s regulation of catalysis from biocircuits to metabolism\nby Fangzhou
Xiao (Caltech) as part of Seminar on Biological Control Systems\n\nAbstrac
t: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/10/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Jean-Baptiste Lugagne (Boston University)
DTSTART:20220830T150000Z
DTEND:20220830T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/11
DESCRIPTION:Title: High-throughput single-cell control using real-time feedback\nby J
ean-Baptiste Lugagne (Boston University) as part of Seminar on Biological
Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/11/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Edward Hancock (University of Sydney)
DTSTART:20220726T150000Z
DTEND:20220726T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/12
DESCRIPTION:Title: Stabilization of anthitetic control via molecular buffering\nby Ed
ward Hancock (University of Sydney) as part of Seminar on Biological Contr
ol Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/12/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Filo Maurice (ETH-Zurich)
DTSTART:20220628T150000Z
DTEND:20220628T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/13
DESCRIPTION:Title: A hierarchy of biomolecular proportional-integral-derivative feedback
controllers for robust adaptation and dynamic performance\nby Filo Mau
rice (ETH-Zurich) as part of Seminar on Biological Control Systems\n\nAbst
ract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/13/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Chelsea Hu (Caltech)
DTSTART:20220531T150000Z
DTEND:20220531T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/14
DESCRIPTION:Title: Layered feedback control overcomes performance trade-off in synthetic
biomolecular networks\nby Chelsea Hu (Caltech) as part of Seminar on B
iological Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/14/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Michaelle N Mayalu (Stanford University)
DTSTART:20220426T150000Z
DTEND:20220426T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/15
DESCRIPTION:Title: Analysis and design of paradoxical feedback circuits for homeostasis o
f cell concentration\nby Michaelle N Mayalu (Stanford University) as p
art of Seminar on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/15/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Rogelio Hernandez-Lopez (UCSF)
DTSTART:20220329T150000Z
DTEND:20220329T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/16
DESCRIPTION:Title: T cell circuits that sense antigen density with an ultrasensitive thre
shold\nby Rogelio Hernandez-Lopez (UCSF) as part of Seminar on Biologi
cal Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/16/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Ankit Gupta (ETH-Zurich)
DTSTART:20220222T160000Z
DTEND:20220222T170000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/17
DESCRIPTION:Title: Frequency Spectra and the Color of Cellular Noise\nby Ankit Gupta
(ETH-Zurich) as part of Seminar on Biological Control Systems\n\nAbstract:
TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/17/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Christian Cuba Samaniego (UCLA)
DTSTART:20220125T160000Z
DTEND:20220125T170000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/18
DESCRIPTION:Title: Engineering synthetic networks for pattern recognition in mammalian ce
lls\nby Christian Cuba Samaniego (UCLA) as part of Seminar on Biologic
al Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/18/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Yitong Ma (Caltech)
DTSTART:20211217T160000Z
DTEND:20211217T170000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/19
DESCRIPTION:Title: Synthetic mammalian signaling circuits for robust cell population cont
ro\nby Yitong Ma (Caltech) as part of Seminar on Biological Control Sy
stems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/19/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Ania Baetica (UCSF)
DTSTART:20211119T160000Z
DTEND:20211119T170000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/20
DESCRIPTION:Title: Analysis and parameter identification of four incoherent feedforward l
oop circuit designs\nby Ania Baetica (UCSF) as part of Seminar on Biol
ogical Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/20/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Mariana Gomez-Schiavon (National Autonomous University of Mexico)
DTSTART:20211029T150000Z
DTEND:20211029T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/21
DESCRIPTION:Title: Cora - A general approach for quantifying biological feedback control<
/a>\nby Mariana Gomez-Schiavon (National Autonomous University of Mexico)
as part of Seminar on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/21/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Yili Qian (University of Wisconsin-Madison)
DTSTART:20210924T150000Z
DTEND:20210924T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/22
DESCRIPTION:Title: Decentralized control for robustness of gene networks to unintended in
teractions\nby Yili Qian (University of Wisconsin-Madison) as part of
Seminar on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/22/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Noah Olsman (Harvard University)
DTSTART:20210828T150000Z
DTEND:20210828T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/23
DESCRIPTION:Title: Closing the gap between theory and experiments in the design of biomol
ecular feedback circuits\nby Noah Olsman (Harvard University) as part
of Seminar on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/23/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Ross Jones (University of British Columbia)
DTSTART:20210730T150000Z
DTEND:20210730T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/24
DESCRIPTION:Title: Robust and tunable signal processing in mammalian cells via engineered
covalent modification cycles\nby Ross Jones (University of British Co
lumbia) as part of Seminar on Biological Control Systems\n\nAbstract: TBA\
n
LOCATION:https://researchseminars.org/talk/Biocontrol/24/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Brayden Kell (University of Toronto)
DTSTART:20230725T150000Z
DTEND:20230725T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/25
DESCRIPTION:Title: Noise properties of adaptation-conferring biochemical control modules<
/a>\nby Brayden Kell (University of Toronto) as part of Seminar on Biologi
cal Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/25/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Zachary Fox (Oak Ridge National Lab)
DTSTART:20231128T160000Z
DTEND:20231128T170000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/26
DESCRIPTION:Title: Single cell control using Finite State Projection based Bayesian Filte
rs\nby Zachary Fox (Oak Ridge National Lab) as part of Seminar on Biol
ogical Control Systems\n\n\nAbstract\nBiotechnology is rapidly improving\,
largely due to our ability to manipulate genetic material and efficiently
measure biological processes. This talk will describe advances in computa
tional approaches and experimental platforms to probe and control stochast
ic biological processes within individual cells under a microscope. I will
first describe how the finite state projection approach to solving the ch
emical master equation can be used to estimate the amount of protein in a
cell given fluorescence measurements. Then\, I will show a novel platform
for interfacing individual cells with computational models of gene express
ion using optogenetics. Chemical master equation-based Bayesian filters ar
e used to perform state estimation and control the gene expression in each
cell independently. I will also discuss how such systems could be used to
design experiments to better identify model parameters.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/26/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Jakob Ruess (Inria Paris & Institut Pasteur)
DTSTART:20231219T160000Z
DTEND:20231219T170000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/27
DESCRIPTION:Title: From single cells to microbial consortia and back: stochastic chemical
kinetics coupled to population dynamics\nby Jakob Ruess (Inria Paris
& Institut Pasteur) as part of Seminar on Biological Control Systems\n\n\n
Abstract\nAbstract. At the single-cell level\, biochemical processe
s are inherently stochastic. Such processes are typically studied using mo
dels based on stochastic chemical kinetics\, governed by a chemical master
equation (CME). The CME describes the time evolution of the probability d
istribution over system states and has been a tremendously helpful tool in
shedding light on the functioning of cellular processes. However\, single
cells are not living in isolation but are part of a growing population or
community. In such contexts\, stochasticity at the single-cell scale lead
s to population heterogeneity and cells may be subject to population proce
sses\, such as selection\, that drive the population distribution away fro
m the probability distribution of the single-cell process.\nHere\, I will
introduce a multi-scale modeling framework that allows one to capture coup
led stochastic single-cell and population process. I will show that the ex
pected population distribution of such multi-scale models can be calculate
d by solving a modified version of the CME that is of the same dimensional
ity as the standard CME. I will then show how such models can be used to e
xplain experimental data on plasmid copy number fluctuations and populatio
n growth in media that selects against cells that have lost the plasmid. F
inally\, I will present an optogenetic recombination system that allows on
e to partition yeast populations into different cell types via external ap
plication of blue light to cells and show how our modeling framework can b
e used to predict and control emerging dynamics of the population composit
ion in response to time-varying light stimuli.\n\nBio.\nJakob Ruess
received his PhD in 2015 from the Automatic Control Laboratory at ETH Zur
ich\, Switzerland\, where he worked under the supervision of John Lygeros
on using moment equations of stochastic reaction networks for problems suc
h as parameter inference and experimental design. He moved on to IST Austr
ia for a postdoc where he worked together with Remy Chait\, Gasper Tkacik
and Calin Guet to realize the first study on optogenetic feedback control
of gene expression dynamics inside single cells. Since 2016\, he is a perm
anent researcher at the French National Institute for Research in Computer
Science and Automation (Inria). In 2022\, he received an ERC Starting Gra
nt\, entitled BridgingScales\, which aims to study the dynamics of coupled
stochastic single-cell and population processes.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/27/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Anna-Maria Makri Pistikou (TU Eindhoven)
DTSTART:20240227T160000Z
DTEND:20240227T170000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/28
DESCRIPTION:Title: Engineering synthetic communication in mammalian cells\nby Anna-Ma
ria Makri Pistikou (TU Eindhoven) as part of Seminar on Biological Control
Systems\n\n\nAbstract\nAbstract. The ability to engineer novel fun
ctions into mammalian cells has become a key force in biomedical research\
, revolutionizing the field of cell diagnostics and therapeutics. In detai
l\, the rational design and implementation of synthetic\, orthogonal mamma
lian sender-receiver consortia has the potential to unravel fundamental de
sign principles of cell communication circuits and offers a framework for
engineering of designer cell consortia with potential applications in cell
therapeutics and artificial tissue engineering. This talk will detail the
development of an orthogonal\, and scalable mammalian synthetic intercell
ular communication platform that exploits the programmability of synthetic
receptors and selective affinity and tunability of diffusing coiled-coil
(CC) peptide heterodimers\, referred to as CC-GEMS. Leveraging the ability
of CCs to exclusively bind to a selected cognate receptor\, we demonstrat
e orthogonal receptor activation\, as well as Boolean logic operations at
the receptor level. We show intercellular communication based on synthetic
CC-GEMS receptors and secreted multidomain coiled-coil (CC) ligands and d
emonstrate a minimal\, three-cell population system that can perform distr
ibuted AND gate logic. Lastly\, we show CC-GEMS receptor-dependent therape
utic protein expression. Our work provides a blueprint for the engineering
of complex cell consortia\, with the potential to expand the aptitude of
cell therapeutics and diagnostics.\n\nBio. Anna-Maria Makri Pistiko
u earned a bachelor’s degree in nursing science from the University of P
eloponnese in 2014. She continued her studies at Maastricht University\, w
here she obtained a bachelor’s degree in cell and molecular biology in 2
016 and a research master’s degree in Cognitive and Clinical Neuroscienc
e\, specializing in Fundamental Neuroscience\, in 2018. Currently\, she is
commencing her doctoral studies in collaboration with the Institute of Co
mplex Molecular Science at the Technical University of Eindhoven. Her rese
arch interests primarily focus on the utilization of synthetic receptors a
s tools to engineer biological structures capable of meeting human needs.\
n
LOCATION:https://researchseminars.org/talk/Biocontrol/28/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Charlotte Bunne (ETH-Zurich & ETH AI Center)
DTSTART:20240116T160000Z
DTEND:20240116T170000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/29
DESCRIPTION:Title: Predicting Single-Cell Drug Responses using Optimal Transport\nby
Charlotte Bunne (ETH-Zurich & ETH AI Center) as part of Seminar on Biologi
cal Control Systems\n\n\nAbstract\nCell populations are almost always hete
rogeneous in function and fate. To understand a patient’s responses to m
olecular drugs and design efficient treatments\, it is vital to recover th
e underlying population dynamics and fate decisions of single cells upon p
erturbation. However\, measuring features of single cells requires destroy
ing them. As a result\, a cell population can only be monitored with seque
ntial snapshots\, obtained by sampling a few particles that are sacrificed
in exchange for measurements. In order to reconstruct individual cell fat
e trajectories\, as well as the overall dynamics\, one needs to re-align t
hese unpaired snapshots\, in order to guess for each cell what it might ha
ve become at the next step.\n\nOptimal transport theory can provide such m
aps\, and reconstruct these incremental changes in cell states over time.
This celebrated theory provides the mathematical link that unifies the sev
eral contributions to model cellular dynamics that we present here: Infere
nce from data of an energy potential best able to describe the evolution o
f perturbation responses (Bunne et al.\, 2022a) building on the Jordan-Kin
derlehrer-Otto (JKO) flow\; recovery of differential equations modeling th
e stochastic transitions between cell fates in developmental processes (Bu
nne et al.\, 2022b)\; as well as zero-sum game theory models parameterizin
g distribution shifts upon interventions\, which we employ to model hetero
geneous responses of tumor cells to cancer drugs (Bunne et al.\, 2021).\n\
nThis work thus provides an overview on how we can employ machine learning
algorithms to robustly learn optimal transport models\, and how this enha
nces current drug discovery and treatment design.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/29/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Alice Boo (MIT)
DTSTART:20240326T160000Z
DTEND:20240326T170000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/30
DESCRIPTION:Title: Burden-Driven Multicellular Control Feedback for Microbial Consortia\nby Alice Boo (MIT) as part of Seminar on Biological Control Systems\n\
n\nAbstract\nAbstract. Abstract:\nDivision of labor can reduce the
burden caused by expressing large metabolic pathways. It allows to select
and design the optimal strains for enzyme expression of the pathway of int
erest to improve yields and titres. However\, multicellular feedback contr
ol strategies could also be an asset to improve productivity of microbial
consortia. In this work\, we connected two E. coli strains such that if on
e was growing faster than the other\, expression burden would slow down gr
owth and stabilise the growth differences between the strains. We showed t
hat burden could be successfully used to balance community composition. In
terestingly\, our co-culture control mechanism did not reduce the final pr
oduct yields in either strain. Instead\, it actually enhanced them\, impro
ving the final yield by 81% in the slowest-growing strain and by 35% in th
e fastest-growing strain\, compared to a co-culture that did not have a co
mmunity control mechanism. This project provided a fundamental basis to ex
plore the importance of multicellular feedback control strategies as mecha
nisms to improve the efficiency of division of labour to produce high-valu
e compounds for metabolic engineering.\n\nBio. Alice is a postdoc i
n the Voigt Lab at MIT. Previously\, she did her PhD jointly in the Prof G
uy-Bart Stan’s Control Synthetic Biology lab and Dr Rodrigo Ledesma Amar
o’s Synthetic Biology for Metabolic Engineering lab. She focused on engi
neering multicellular feedback systems for metabolic engineering. Now her
research focuses on building cross-kingdom multicellular systems for biore
mediation and environmental challenges using plants and their native root
microbiome.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/30/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Ying Tang (Institute of Fundamental and Frontier Sciences\, Univer
sity of Electronic Sciences and Technology of China\, Chengdu)
DTSTART:20240430T140000Z
DTEND:20240430T150000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/31
DESCRIPTION:Title: Neural-network solutions to stochastic reaction networks\nby Ying
Tang (Institute of Fundamental and Frontier Sciences\, University of Elect
ronic Sciences and Technology of China\, Chengdu) as part of Seminar on Bi
ological Control Systems\n\n\nAbstract\nAbstract. Machine learning
and stochastic dynamics have deep connections and cross-feed each other. A
s an example\, I will report our recent progress in tracking the time evol
ution of the probability distribution for stochastic reaction networks. We
propose a machine learning approach using a variational autoregressive ne
twork to solve the chemical master equation. We apply the approach to exam
ples in computational biology\, where it accurately generates the probabil
ity distribution over time. The results suggest a general approach towards
tracking large chemical reaction networks based on modern machine learnin
g.\n\nBio. Dr. Ying Tang's research interests are stochastic dynami
cs\, machine learning\, and statistical physics. Since 2024\, he is Profes
sor at the Institute of Fundamental and Frontier Sciences\, University of
Electronic Sciences and Technology of China\, Chengdu. From 2021 to 2024\,
he was an Associate researcher in Beijing Normal University\, Zhuhai. Fro
m 2018 to 2021\, he was a postdoctoral fellow at UCLA. He received a PhD i
n physics from Shanghai Jiao Tong University in 2018 and a bachelor degree
from Zhiyuan College\, Shanghai Jiao Tong University in 2013.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/31/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Sally Wang (UMD)
DTSTART:20240528T150000Z
DTEND:20240528T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/32
DESCRIPTION:Title: Electrogenetics and Electro-biofabrication Enable Realization of the "
Internet of Bio-Nano Things\nby Sally Wang (UMD) as part of Seminar on
Biological Control Systems\n\n\nAbstract\nAbstract. With the rise
of concepts like the “Internet of Things” and the advances in electron
ic technologies\, our lives have now been occupied with smart devices that
easily communicate with one another. These devices\, however\, lack the a
bility to freely exchange information with the world of biology\, since el
ectronics and biology possess very different communication modalities. We
recently introduced “electrogenetics” including an electrogenetic CRIS
PR (eCRISPR) that mediates the “conversation” between electrodes and g
enetic networks by tapping into the oxyRS oxidative stress response regulo
n of E. coli.\n\nIn this work\, we expanded the electrogenetic framework a
nd established a complete network of Bio-Nano Things\, which collectively
allowed automated\, algorithm-based feedback control of electrogenetic CRI
SPR activity with remote input from both a distant electronically-controll
ed enzyme- on-a-chip as well as a cell phone. First\, we created an abioti
c/biotic interface in order to improve information transfer between electr
onics and biological systems. Inspired by nature\, using electrobiofabrica
tion\, we created an “artificial biofilm” that immobilized living cell
s on an electrode’s surface\, creating a “living electrode” by elect
rochemically assembling bacteria and thiolated polyethylene glycol (PEG-SH
) to form a thin hydrogel film. Next\, we developed an oxyRS-based eCRISPR
to more efficiently traverse the abiotic and biotic domains\, reduce barr
iers accompanying diverse biological languages\, and broaden the bandwidth
of electrochemical signaling\, together allowing multiplexed transcriptio
nal regulation on various genetic targets. These include two crucial quoru
m sensing (QS) genes that controlled the relay of electrochemical signals
to a broader yet selective audience of microbial populations through QS co
mmunication. We then integrated the engineered interface and eCRISPR withi
n “BioSpark”\, a full electrogenetic system including custom-made hard
ware and software\, for algorithm-governed automated control of gene expre
ssion wherein electronic inputs and optoelectronic outputs provide for ful
ly programmable electronic I/O. Finally\, we demonstrated a network of Bio
-Nano Things by connecting the BioSpark system with another bio-electroche
mical device and human “users” to achieve remote feedback control of e
CRISPR activity and more importantly\, multidirectional communication betw
een living systems regardless of physical distance. In sum\, our network e
nabled seamless guidance of biological processes and communities with an e
lectronic input but also the conferment and digitization of biological out
put to an electronic signal\, realizing an “all-connected” network of
biological systems.\n\n\nBio. Sally Wang is currently a postdoc res
earch associate at the University of Maryland\, College Park under the gui
dance of Prof. William E. Bentley. She obtained her B.S. from National Tai
wan University and her Ph.D. from University of Maryland\, College Park (B
entley Lab). Her research interests include using synthetic biology tools
to engineer communication routes between biological systems and electronic
s\, as well as investigating the behavior of biological systems at the abi
otic/biotic interface. She will soon begin her postdoctoral research at Pr
inceton University this summer with the Avalos lab\, using electrogenetics
to address metabolic engineering challenges in yeast systems.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/32/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Nam Tran (Drexel University)
DTSTART:20240625T150000Z
DTEND:20240625T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/33
DESCRIPTION:Title: Transfer function of network motifs and what they tell us about signal
processing in cells\nby Nam Tran (Drexel University) as part of Semin
ar on Biological Control Systems\n\n\nAbstract\nAbstract.\n\nPar
t 1: Transfer function of biochemical network motifs\n\nNetwork motifs
are thought to have special signal processing functions. Biological signa
ls are often delivered in oscillations and pulses. Therefore\, it is usefu
l to understand the signal processing functions of network motifs in respo
nse to oscillations and pulses. One tool to understand this is the transfe
r function\, which allows us to view the dynamics of these motifs from a f
requency domain perspective. We present the transfer function for a select
ion of motifs. We show how each motif exhibits different filtering propert
ies and highlight their potential roles in signaling within the cell.\n\n<
b>Part 2: Sensitivity function of biochemical feedback loops\n\nFeedba
ck loops allow biological systems to effectively respond to their changing
environment. However\, the biochemical conditions that make up these feed
back loop mechanisms can vary. Quantifying how robust these feedback loops
are to such variations can help us understand how well biological systems
implement feedback. Previous research has found that cells might commonly
use negative feedback because it allocates the sensitivity to parameters
that are unlikely to vary such as cooperative binding\, while remaining in
sensitive to parameters such as production and degradation rates. In this
research\, we performed sensitivity analysis on feedback loops consisting
of one and two species involving combinations of positive and negative fee
dback. Our analysis can provide insight into how synthetic biological circ
uits can be reliably designed and used in changing environments. \n\n\n
Bio. Nam is currently a postdoc at Drexel University under Prof. Ania-
Ariadna Baetica. He obtained his B.S. at the University of Melbourne (Aust
ralia) and PhD at Swinburne University (Australia). His current research i
nterests include studying robustness of biological feedback loops\, and wa
ys to generalise this for arbitrary dynamics and feedback architectures. N
am enjoys talking about control theory and dynamical systems and physical
models in biology\, so please don't be shy to reach out if you want to cha
t!\n
LOCATION:https://researchseminars.org/talk/Biocontrol/33/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Kirill Sechkar (University of Oxford)
DTSTART:20240730T150000Z
DTEND:20240730T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/34
DESCRIPTION:Title: Modelling for resource-aware analysis and design of synthetic gene cir
cuits in bacteria\nby Kirill Sechkar (University of Oxford) as part of
Seminar on Biological Control Systems\n\n\nAbstract\nSynthetic genes comp
ete for resources among themselves and with the host cell's native genes\,
burdening the host and impeding its growth. These resource couplings\, ex
hibited by a wide range of biological processes\, can give rise to unexpec
ted behaviours and impair biotechnologies' predictability\, modularity\, e
fficiency\, and functional lifespan. \n\nIn this talk\, I will provide an
overview of our work on using mathematical modelling to understand and for
ecast resource competition phenomena\, as well as to mitigate their unwant
ed effects on synthetic gene circuit performance in bacteria. First\, we d
escribe our recently published resource-aware bacterial cell model\, devel
oped to realistically capture competition for ribosomes whilst maintaining
maximum ease of gene circuit design and analysis. This model is then used
to propose and examine the performance of a novel versatile biomolecular
controller aimed at preventing the loss of engineered functionalities by e
ngineered cell populations. Second\, we showcase how resource-aware modell
ing of RNA-based circuits can help to elucidate their behaviour and explai
n unexpected experimental outcomes.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/34/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Ted Grunberg (MIT)
DTSTART:20240827T150000Z
DTEND:20240827T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/35
DESCRIPTION:Title: Error bounds for the linear noise approximation to stationary distribu
tions of chemical reaction networks\nby Ted Grunberg (MIT) as part of
Seminar on Biological Control Systems\n\n\nAbstract\nBiomolecules interact
ing according to a chemical reaction network are often modeled by a contin
uous time Markov chain that describes the evolution of counts of the biomo
lecules over time. Such Markov chains typically have a large or infinite n
umber of states and are thus computationally difficult to analyze. Therefo
re\, approximations exploiting the fact that the volume and molecular coun
ts are both large are often used. The most common such approximations are
the reaction rate equations (RREs)\, which are a deterministic model\, and
the linear noise approximation (LNA)\, which is a diffusion approximation
to fluctuations about the solution of the RREs. Limit theorem results\, d
ue to Kurtz (1971)\, establish the validity of the RREs and of the LNA for
finite times. However\, such results do not justify approximating the sta
tionary distribution of a chemical reaction network using the RREs or LNA.
The validity of these approximations for the stationary distribution has
only been investigated for special cases\, such as when the Markov chain
’s state space is bounded in concentration\, or when the chemical reacti
on network has a special structure. Here\, we use Stein’s method to deri
ve bounds on the approximation error for the LNA applied to the stationary
distribution of a chemical reaction network. Specifically\, we give a non
-asymptotic bound on the 1-Wasserstein distance between an appropriately s
caled Markov chain and its LNA\, under certain technical conditions\, that
decays to zero with increasing system size. We further show how global st
ability properties of an equilibrium point of the RREs are sufficient to o
btain such error bounds. Our results can be used to check when the LNA is
a suitable approximation of the stationary distribution of a chemical reac
tion network without having to perform computationally costly simulations.
\n
LOCATION:https://researchseminars.org/talk/Biocontrol/35/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Davide Salzano
DTSTART:20240924T150000Z
DTEND:20240924T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/36
DESCRIPTION:Title: In-vivo distributed multicellular control of gene expression in synthe
tic microbial consortia\nby Davide Salzano as part of Seminar on Biolo
gical Control Systems\n\n\nAbstract\nCybergenetics is an emerging discipli
ne at the interface between synthetic biology and control engineering\, ai
med at exploiting feedback control to engineer reliable and robust synthet
ic biological circuits to regulate and dynamically tune the expression of
a target gene in the host organism. Both E.coli and mammalian cells have b
een engineered so as to realize feedback control loops that regulate gene
expression intracellularly (a strategy known as embedded control). However
\, embedded controllers have several limitations\, including modularity\,
as any change in the controller design requires a complete re-engineering
of the designed gene network.\nA solution to overcome these problems is to
distribute the required functionalities to different populations such tha
t each of them carries out a specific task. This control paradigm\, known
as multicellular control\, relies on engineering a Controller population t
hat senses and computes a control action used to regulate in real-time the
state of a process hosted in a second population\, denoted as Targets. In
this talk I will present a possible biological implementation and experim
ental validation of Controllers and Targets in E.coli. Specifically\, the
response of both populations has been characterized\, showing that they ca
n establish effective communication between each other and influence their
behaviour so the Targets can achieve the desired behaviour decided by the
controllers. Additionally\, I will show clear evidence that the architect
ure allows for tunable regulation of a desired gene in the Targets\, and t
hat such regulation is robust to perturbations such as imbalances between
the size of the two populations. The developed architecture can enable the
realisation of robust modules with potential application in biomedicine a
nd industrial bioproduction.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/36/
END:VEVENT
BEGIN:VEVENT
SUMMARY:María Cristina Cannarsa (Sapienza Università di Roma)
DTSTART:20241029T150000Z
DTEND:20241029T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/37
DESCRIPTION:Title: Light-driven synchronization of optogenetic clocks\nby María Cris
tina Cannarsa (Sapienza Università di Roma) as part of Seminar on Biologi
cal Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/37/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Fengjie Zhao (USC)
DTSTART:20241210T160000Z
DTEND:20241210T170000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/38
DESCRIPTION:Title: Control of extracellular electron transfer in phylogenetically diverse
electroactive bacteria\nby Fengjie Zhao (USC) as part of Seminar on B
iological Control Systems\n\n\nAbstract\nExtracellular electron transfer (
EET) is a process that allows electroactive bacteria to route electrons fr
om the cellular interior to external electron acceptors under anaerobic co
nditions. Shewanella oneidensis MR-1\, which can respire external minerals
\, is a model electroactive microorganism and utilizes a network of multih
eme c-type cytochromes for EET. In addition\, S. oneidensis MR-1 is able t
o form living conductive biofilms for long-distance electron transport. He
re\, we introduced optogenetic circuits into S. oneidensis to control elec
tron transfer at different scales. We first developed a lithographic strat
egy to pattern the conductive biofilms of S. oneidensis on electrodes by a
blue light-induced genetic circuit\, which allowed us to demonstrate tuna
ble conduction of living biofilms dependent on pattern geometry. Next\, we
developed a red light-induced genetic circuit in S. oneidensis based on a
reported iLight system. This red light-induced genetic circuit was used t
o control cytochrome expression and EET activity in S. oneidensis with lig
ht. Beyond environmental mineral-respiring bacteria\, recent studies have
also suggested that some microbes in the human gut are capable of EET thro
ugh a flavin-based EET mechanism\, despite being flavin auxotrophs. To bro
aden and deepen our understanding of EET in the gut microbial community\,
we performed electrochemical measurements on co-cultures of Enterococcus f
aecalis OG1RF and Escherichia coli MG1655. The results showed that E. faec
alis used flavins that are secreted by E. coli as electron shuttles to med
iate EET. Our studies reveal a synergistic mechanism that modulates EET ac
tivity in the gut microbial community.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/38/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Gennady Gorin (Caltech)
DTSTART:20231107T160000Z
DTEND:20231107T170000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/39
DESCRIPTION:Title: Stochastic foundations for single-cell RNA sequencing\nby Gennady
Gorin (Caltech) as part of Seminar on Biological Control Systems\n\n\nAbst
ract\nSingle-cell RNA sequencing\, which quantifies cell transcriptomes\,
has seen widespread adoption\, accompanied by a proliferation of analytic
methods. However\, there has been relatively little systematic investigati
on of its best practices and their underlying assumptions\, leading to cha
llenges and discrepancies in analysis. I motivate a set of generic\, princ
ipled strategies for modeling the biological and technical stochasticity i
n sequencing experiments\, and use case studies to illustrate their prospe
cts for the discovery and interpretation of biophysical kinetics.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/39/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Giuliano De Carluccio (MIT)
DTSTART:20240206T160000Z
DTEND:20240206T170000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/40
DESCRIPTION:Title: The CASwitch: a synthetic biology solution for high-performance induci
ble gene expression systems in biotechnology\nby Giuliano De Carluccio
(MIT) as part of Seminar on Biological Control Systems\n\n\nAbstract\n
Abstract. Achieving tight and reliable control of gene expression in l
iving cells is crucial for the practical application of synthetic biology.
While transcriptional-based inducible gene systems are widely used in syn
thetic biology\, they often suffer from shortcomings\, including unintende
d background gene expression (leakiness). Traditional approaches to enhanc
e these systems involves iterative screening of transcription factor and p
romoter libraries\, facing challenges in finding the right balance between
leakiness and maximal induced expression\, and being ad-hoc solutions.\n\
nIn this seminar\, I will discuss how control theory\, coupled with a quan
titative synthetic biology approach\, offers a general solution to enhance
the performance of transcriptional-based inducible gene systems without m
odifying the transcription factor (TF) or its promoter. I will show how a
combination of Coherent Feed-Forward Loop (CFFL) and Mutual Inhibition (MI
) network motifs\, biologically implemented through a CasRx endoribonuclea
se\, results in the development of a mammalian synthetic gene circuit achi
eving quasi-zero leakiness while maintaining high levels of expression\; t
hat we named CASwitch. Finally\, I will showcase the versatility of the CA
Switch through three different applications\, including enhancing the sens
itivity of a whole-cell biosensor\, regulating the expression of a toxic g
ene\, and facilitating the inducible production of Adeno-Associated Virus
(AAV) vectors.\n\nThis talk offers insights into the design of synthetic g
ene circuits as a means to improve existing inducible gene expression syst
ems\, providing tight and reliable control over gene expression for real-w
orld applications.\n\nBio. Giuliano De Carluccio is a Postdoctoral
Researcher in the Collins Lab at MIT\, working on the development of RNA-
based devices to control gene expression in the field of mRNA therapeutics
. He earned his Ph.D. in Industrial Bioengineering in 2023 from the Univer
sity of Naples Federico II. During his PhD studies\, he worked with Diego
di Bernardo at the Telethon Institute of Genetic and Medicine in Naples\,
employing quantitative synthetic biology and mathematical modeling to desi
gn a new gene expression control system in mammalian cells for real-world
applications.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/40/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Massimo Bellato (University of Padova)
DTSTART:20250128T160000Z
DTEND:20250128T170000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/41
DESCRIPTION:Title: From bacterial communication to tackle Antimicrobial Resistance (AMR)<
/a>\nby Massimo Bellato (University of Padova) as part of Seminar on Biolo
gical Control Systems\n\n\nAbstract\nThe increasing resistance of bacteria
to antimicrobials poses a significant challenge for public health. Howeve
r\, while the pursuit of new antimicrobial agents is often outpaced by the
rapid development of bacterial resistance\, synthetic biology can offer i
nnovative tools to combat this issue. This seminar will explore an ongoing
project that starting from a systems biology approach to investigate the
properties of bacterial communication equilibrium\, has has led to the inv
estigation of complementary strategies to disrupt AMR-associated mechanism
s\, including (i) the degradation of external signaling molecules\, (ii) C
RISPR interference in pathogenic organisms\, and (iii) delivery systems de
signed to transfer therapeutic genetic circuits into target cells.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/41/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Takehiro Tottori (RIKEN)
DTSTART:20250225T140000Z
DTEND:20250225T150000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/42
DESCRIPTION:Title: Theory for Optimal Estimation and Control under Resource Limitations a
nd Its Applications to Biological Information Processing and Decision-Maki
ng\nby Takehiro Tottori (RIKEN) as part of Seminar on Biological Contr
ol Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/42/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Josiah Passmore (Utrecht University)
DTSTART:20250325T150000Z
DTEND:20250325T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/43
DESCRIPTION:Title: Outcome-Driven Microscopy: Closed-Loop Optogenetic Control of Cell B
iology\nby Josiah Passmore (Utrecht University) as part of Seminar on
Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/43/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Sebastian Castillo-Hair (University of Washington)
DTSTART:20250429T150000Z
DTEND:20250429T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/44
DESCRIPTION:Title: Generalizable design of human tissue\, cell type\, and cell state-spec
ific gene expression via deep learning models of genomic accessibility\nby Sebastian Castillo-Hair (University of Washington) as part of Semina
r on Biological Control Systems\n\n\nAbstract\nCells across tissues\, deve
lopmental stages\, and disease conditions adopt distinct \nintracellular s
tates – epigenomic\, transcriptomic\, and proteomic profiles – to \nco
mpartmentalize function in time and space. The ability to write DNA- and R
NA-\nencoded programs that sense and interface with cellular states has tr
ansformative \npotential for biotechnology\, for example in developing gen
e therapies with tissue\, \ncell type\, and disease-specificity to minimiz
e off-target effects\, and in guiding stem \ncells towards differentiated
cell states for regenerative medicine. However\, our \nlimited understandi
ng of how basic cellular processes\, such as gene expression\, \nare regul
ated in different cellular states hinders any attempt at rationally \ndesi
gning such genetic programs. Neural network (NN) and generative models \nt
hat capture different aspects of cell state regulation from large omics da
tasets \noffer a powerful tool to overcome these barriers.\n\nHere\, we pr
esent our recent work on programming cell type- and state-specific \ngene
expression via synthetic enhancers – short DNA elements that regulate \n
transcription. We trained NN models on genomic accessibility data\, based
on the \nrationale that active enhancers reside in genomic regions with an
open\, accessible \nchromatin state. These data are available for hundred
s of human cell types and \ntissues and thus offer a vast resource for enh
ancer design. Using data of >3 million\nDNase-hypersensitive sites across
733 cell types and tissues\, we trained NN \nmodels to predict accessibili
ty from sequence and used them to design de novo \nsequences with cell typ
e-specific accessibility. To validate our designs\, we tested a \nlibrary
of 9\,000 synthetic enhancers in a panel of 10 human cell lines – includ
ing \nHepG2 (liver)\, K562 (lymphoid)\, SJCRH30 (muscle)\, WERI-Rb1 (retin
a)\, and MCF7 \n(breast) – as well as in vivo in mouse retinas. In most
cases\, synthetic sequences \nshowed significantly higher enhancer activit
y and specificity in their target cells \ncompared to control genomic enha
ncers. Our results demonstrate that NN models \nof genomic accessibility c
an be used to program gene expression specific to a large\nvariety of cell
types\, highlighting the potential of NN-driven design for synthetic \nbi
ology.\n\nBio. Sebastian is a postdoctoral scholar at the ECE Depar
tment\, working in Georg Seelig’s lab. Sebastian’s research focuses on
synthetic biology\, specifically on using high-throughput assays and deep
learning methods to understand how untranslated mRNA sequences regulate t
ranslation and stability in human cells\, and to engineer improved sequenc
es for therapeutics applications. Before\, Sebastian earned his Ph.D. in B
ioengineering at Rice University\, where he worked on optogenetics and bac
terial synthetic biology.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/44/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Maren Philipps (e Friedrich-Wilhelms-Universität Bonn\, Bonn\, Ge
rmany)
DTSTART:20250527T150000Z
DTEND:20250527T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/45
DESCRIPTION:Title: Universal differential equations for systems biology: Current state an
d open problems\nby Maren Philipps (e Friedrich-Wilhelms-Universität
Bonn\, Bonn\, Germany) as part of Seminar on Biological Control Systems\n\
nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/45/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Eric De Giuli (University of Toronto)
DTSTART:20250624T150000Z
DTEND:20250624T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/46
DESCRIPTION:Title: Noise equals endogenous control\nby Eric De Giuli (University of T
oronto) as part of Seminar on Biological Control Systems\n\n\nAbstract\nSt
ochastic systems have a control-theoretic interpretation in which noise pl
ays the role of endogenous control. In the weak-noise limit\, relevant at
low temperatures or in large populations\, control is optimal and an exact
mathematical mapping from noise to control can be drawn. I will explain t
his mapping in simple language and argue that it is particularly relevant
for multistable chemical reaction networks\, where it can build intuition
for why biological mechanisms can work better in the presence of noise\; a
nd how agentic behavior emerges naturally without recourse to mysticism.\n
\nBio: Eric De Giuli obtained his Hon.BSc with High Distinction in
Mathematics and Physics from the University of Toronto in 2006. At UBC\, h
e obtained a MSc in Geophysics (2009) and a Ph.D. in Applied Mathematics (
2013)\, on turbulence\, and granular matter\, respectively. As a postdocto
ral fellow in Matthieu Wyart's group at NYU and then EPFL\, he worked on t
he theory of amorphous solids. From 2017-2019 he was Junior Research Assoc
iate at the Institut Philippe Meyer\, École Normale Supérieure\, Paris
\, where he branched out to apply the tools of disordered systems physics
to other complex systems. In 2019 he returned to Canada as Assistant Profe
ssor (2019-2024) and now Associate Professor (2025-) of Complexity Physics
at Toronto Metropolitan University. His group is now focused on physics m
odels of language and theory for chemical reaction networks\, with applica
tions to biology.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/46/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Daniel Eaton (Harvard Medical School)
DTSTART:20250729T150000Z
DTEND:20250729T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/47
DESCRIPTION:Title: Essentialome-Wide Multigenerational Imaging Reveals Mechanistic Origin
s of Cell Growth Laws\nby Daniel Eaton (Harvard Medical School) as par
t of Seminar on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/47/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Frank Britto Bisso (Carnegie Mellon University)
DTSTART:20250826T150000Z
DTEND:20250826T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/48
DESCRIPTION:Title: Programming genetic circuits that operate as neural networks\nby F
rank Britto Bisso (Carnegie Mellon University) as part of Seminar on Biolo
gical Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/48/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Eugenio Cinquemani (INRIA Grenoble)
DTSTART:20250930T150000Z
DTEND:20250930T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/49
DESCRIPTION:Title: Single-cell data reveal heterogeneity of investment in ribosomes acros
s a bacterial population\nby Eugenio Cinquemani (INRIA Grenoble) as pa
rt of Seminar on Biological Control Systems\n\n\nAbstract\nIn this seminar
I will present our recently published work (Pavlou et al. Nat Commun 16\,
285\, 2025)\, described next.\nRibosomes are responsible for the synthesi
s of proteins\, the major component of cellular biomass. Classical experim
ents have established a linear relationship between the fraction of resour
ces invested in ribosomal proteins and the rate of balanced growth of a mi
crobial population. Very little is known\, however\, about how the investm
ent in ribosomes varies over individual cells in a population. We therefor
e extended the study of ribosomal resource allocation from populations to
single cells\, using a combination of time-lapse fluorescence microscopy
and statistical inference. We found a large variability of ribosome concen
trations and growth rates in conditions of balanced growth of the model ba
cterium Escherichia coli in a given medium\, which cannot be accounted for
by the population-level growth law. A large variability in the allocation
of resources to ribosomes was also found during the transition of the bac
teria from a poor to a rich growth medium. While some cells immediately ad
apt their ribosome synthesis rate to the new environment\, others do so on
ly gradually. Our results thus reveal a range of strategies for investing
resources in the molecular machines at the heart of cellular self-replicat
ion. This raises the fundamental question whether the observed variability
is an intrinsic consequence of the stochastic nature of the underlying bi
ochemical processes or whether it improves the fitness of Escherichia col
i in its natural environment.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/49/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Tuan Pham (University of Amsterdam)
DTSTART:20251028T150000Z
DTEND:20251028T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/50
DESCRIPTION:Title: Adaptation under Dynamic Genotype-Phenotype Map as Out-of-Equilibrium
Learning\nby Tuan Pham (University of Amsterdam) as part of Seminar on
Biological Control Systems\n\n\nAbstract\nGenetic and neural networks are
adaptive - they change slowly in response to the collective states of the
ir constituting elements – genes or neurons. For genotypes encoded by su
ch networks\, adaptation to environmental variations emerges from the requ
irement to reach a predetermined optimal phenotype. By establishing a math
ematical correspondence between this stochastic optimisation process and a
non-equilibrium learning rule for its connections\, we show how a random
gene regulatory network self-organises into a robust structure within an i
ntermediate level of external noise.\n\nBio. Tuan Pham is a fellow
at the Dutch Institute for Emergent Phenomena and the Institute for Theore
tical Physics\, University of Amsterdam. His work focuses on applications
of non-equilibrium statistical physics to complex systems with multiple ti
mescales\, including biological adaptation\, social dynamics and neural ne
tworks.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/50/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Jordi Pla Mauri (CSIC/UPF)
DTSTART:20260127T160000Z
DTEND:20260127T170000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/51
DESCRIPTION:Title: Beyond Reaction: Minimal Genetic Circuits for Cellular Anticipation\nby Jordi Pla Mauri (CSIC/UPF) as part of Seminar on Biological Control
Systems\n\n\nAbstract\nAbstract: Living systems anticipate future conditio
ns to reduce environmental uncertainty—a form of active adaptation found
in both neural and non-neural agents. In this talk\, I present minimal ge
netic circuits inspired by the Moving Average Convergence Divergence princ
iple from finance. By leveraging this simple principle\, these circuits en
able cells to predict environmental trends rather than merely reacting to
changes.\n\nThrough mathematical modeling\, we show that these synthetic c
ircuits generate robust anticipatory responses across diverse conditions.
These results suggest that simple\, evolvable circuits can support biologi
cal prediction\, providing a foundation for engineering sophisticated pred
ictive behaviors in living systems.\n\nBio: Jordi Pla-Mauri is a PhD candi
date at the ICREA–Complex Systems Lab\, Universitat Pompeu Fabra. His re
search leverages synthetic biology to explore distributed computation in c
ell consortia\, criticality in living systems\, and the implementation of
learning motifs and basal cognition in single cells.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/51/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Armin Mohammadie Zand (ETH-Zurich)
DTSTART:20260428T150000Z
DTEND:20260428T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/52
DESCRIPTION:by Armin Mohammadie Zand (ETH-Zurich) as part of Seminar on Bi
ological Control Systems\n\nInteractive livestream: https://mit.zoom.us/j/
94325327926?pwd=TTBMSXlhT2xJT1lzcEM3WTZmTFpBQT09\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/52/
URL:https://mit.zoom.us/j/94325327926?pwd=TTBMSXlhT2xJT1lzcEM3WTZmTFpBQT09
END:VEVENT
BEGIN:VEVENT
SUMMARY:Dongju Lim & Seokhwan Moon (KAIST)
DTSTART:20260224T160000Z
DTEND:20260224T170000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/53
DESCRIPTION:Title: Toward Single-Cell Control: Noise-Robust Perfect Adaptation in Biomole
cular Systems\nby Dongju Lim & Seokhwan Moon (KAIST) as part of Semina
r on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://researchseminars.org/talk/Biocontrol/53/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Jake McGrath (UT Austin)
DTSTART:20260331T150000Z
DTEND:20260331T160000Z
DTSTAMP:20260419T124154Z
UID:Biocontrol/54
DESCRIPTION:Title: Using control theory to study biology: a case study on muscle function
and evolution\nby Jake McGrath (UT Austin) as part of Seminar on Biol
ogical Control Systems\n\n\nAbstract\nBiological systems exhibit a remarka
ble range of dynamical behaviors --- spanning development and repair\, reg
ulation\, sensing and signaling\, motor control\, and adaptation. Powered
by the transduction of stored energy\, these processes enable organisms to
achieve functional goals while maintaining stability far from thermodynam
ic equilibrium. Such dynamics span vast scales in space and time\, from na
nometer-scale molecular motors driving cellular processes to organism-leve
l motion\, and from millisecond reflexes to evolutionary adaptation across
generations.\nWhile physical laws constrain these dynamics\, they do not
fully explain how living systems sense\, decide\, and regulate their behav
ior. In this talk\, I present control theory as a unifying framework for u
nderstanding how biological systems achieve robust\, goal-directed dynamic
s across spatiotemporal scales. I focus on muscle and actin–myosin syste
ms as a model platform\, using a control-theoretic lens to explore how mus
cle-like behavior can inform robotic design\, how nonlinearities shape per
formance tradeoffs\, and how such nonlinearities may arise through biologi
cal evolution.\n
LOCATION:https://researchseminars.org/talk/Biocontrol/54/
END:VEVENT
END:VCALENDAR