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https://www.nist.gov/itl/math/acmd-seminar-quantifying-flows-time-irreversible-markov-chains-application-gene-regulatory

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# ACMD Seminar: Quantifying Flows in Time-Irreversible Markov Chains: Application to a Gene Regulatory Network

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Danielle Middlebrooks*University of Maryland-College Park, Applied Mathematics, Statistics and Scientific Computing Program*

Thursday, August 22, 2019, 3:00 – 4:00 PM	Building 101, Lecture Room B	Gaithersburg

Thursday, August 22, 2019, 1:00 – 2:00PM	Building 1, Room 1107	Boulder

**Host:** Paul Patrone

**Abstract:**Transition path theory (TPT) is a framework used to study the statistical properties of reactive trajectories. Reactive trajectories are those trajectories by which a random walker transits from one subset in the state-space to another disjoint subset. We develop analytical and computational tools based on TPT in order to quantify flows in time-irreversible Markov chains. These tools are applied to a gene regulatory network modeling the dynamics of the Budding Yeast cell cycle.

**Bio:**Danielle Middlebrooks is a doctoral candidate in the Applied Mathematics, Statistics and Scientific Computing (AMSC) program at the University of Maryland-College Park. She received a B.S. in Mathematics from Spelman College in Atlanta, GA. Her research focuses on Markov chain based methods to analyze complex networks. In 2017, she was awarded a COMBINE (Computation and Mathematics for Biological Networks) fellowship: a National Science Foundation-funded Research Traineeship (NRT) program in network biology at the University of Maryland. 

**Note:** Visitors from outside NIST must contact Cathy Graham; (301) 975-3800; at least 24 hours in advance.

Mathematics and statistics

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                -  Paul Patrone  paul.patrone@nist.gov      (301) 975-5551   
                -  Stephen Langer  stephen.langer@nist.gov      (301) 975-5423   

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