Alex H. Lang

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The interspecies exchange of metabolites plays a key role in the spatiotemporal dynamics of microbial communities. This raises the question of whether ecosystem-level behavior of structured communities can be predicted using genome-scale metabolic models for multiple organisms. We developed a modeling framework that integrates dynamic flux balance analysis(More)
A common metaphor for describing development is a rugged "epigenetic landscape" where cell fates are represented as attracting valleys resulting from a complex regulatory network. Here, we introduce a framework for explicitly constructing epigenetic landscapes that combines genomic data with techniques from spin-glass physics. Each cell fate is a dynamic(More)
The deep connection between thermodynamics, computation, and information is now well established both theoretically and experimentally. Here, we extend these ideas to show that thermodynamics also places fundamental constraints on statistical estimation and learning. To do so, we investigate the constraints placed by (nonequilibrium) thermodynamics on the(More)
MicroRNAs are small noncoding RNAs that regulate genes post-transciptionally by binding and degrading target eukaryotic mRNAs. We use a quantitative model to study gene regulation by inhibitory microRNAs and compare it to gene regulation by prokaryotic small non-coding RNAs (sRNAs). Our model uses a combination of analytic techniques as well as(More)
A central goal of synthetic biology is to design sophisticated synthetic cellular circuits that can perform complex computations and information processing tasks in response to specific inputs. The tremendous advances in our ability to understand and manipulate cellular information processing networks raises several fundamental physics questions: How do the(More)
The clinical importance of anterior foregut endoderm (AFE) derivatives, such as thyrocytes, has led to intense research efforts for their derivation through directed differentiation of pluripotent stem cells (PSCs). Here, we identify transient overexpression of the transcription factor (TF) NKX2-1 as a powerful inductive signal for the robust derivation of(More)
Cellular reprogramming, the conversion of one cell type to another, induces global changes in gene expression involving thousands of genes, and understanding how cells globally alter their gene expression profile during reprogramming is an open problem. Here we reanalyze time-course data on cellular reprogramming from differentiated cell types to induced(More)
Here we provide more details of the results in the main text. First, we outline our notation. The time dependent probability of state i is pi = pi(t), while the steady state probability of state i is p ss i . The Laplace transformed probability of state i is Pi(s). The rate to go from state i to state j is kij . The probability to transition from state i to(More)
Sai Teja Pusuluri, Alex H. Lang, 3 Pankaj Mehta, 3 and Horacio E. Castillo 4 Department of Physics and Astronomy and Nanoscale and Quantum Phenomena Institute, Ohio University, Athens, OH, 45701, USA Physics Department, Boston University, Boston, Massachusetts 02215, USA Center for Regenerative Medicine, Boston University, Boston, MA, 02215 Corresponding(More)
Strongly correlated low-dimensional quantum spin models provide a well-established framework to study magnetic properties of insulators, and are of great theoretical interest and experimental relevance in condensed-matter physics. In this thesis, I use quantum Monte Carlo methods to numerically study quantum critical behavior in low-dimensional quantum spin(More)