Research

Research in the Moses Lab

The research projects we pursue typically weave together many threads from disciplines such as evolutionary genetics, systems biology, machine learning, sequence analysis, computer vision, and more. The projects we have pursued over the years reflect the diverse interests of the graduate students and postdocs who worked in the lab. Below is a listing of the main themes that define and guide many of our research projects. For a complete picture of the work that we’ve accomplished, please visit our Publications page.

Evolution and Dynamics of Regulatory Networks

CRZ1 Pulse - Ian Hsu
Zhang & Mangelsdorf 2002
Kompella et al. 2017
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Most complex cellular processes are carried out by groups of genes working together in so-called pathways or networks. We seek to understand how these networks are encoded in genome sequences, how they create dynamic biological phenotypes, and they are created by evolution.

LATEST PAPERS:

Michowski W, Chick JM, Chu C, Kolodziejczyk A, Wang Y, Suski JM, Abraham B, Anders L, Day D, Dunkl LM, Li Cheong Man M, Zhang T, Laphanuwat P, Bacon NA, Liu L, Fassl A, Sharma S, Otto T, Jecrois E, Han R, Sweeney KE, Marro S, Wernig M, Geng Y, Moses A, Li C, Gygi SP, Young RA, Sicinski P Cdk1 Controls Global Epigenetic Landscape in Embryonic Stem Cells Mol Cell. 2020 May 7;78(3):459-476.e13
Cell Press Link PDF Mirror PubMed AbstractArticle
kinase Regulatory Networks transcription factor Proteomics
Mehdi TF, Singh G, Mitchell JA, Moses AM. Variational Infinite Heterogeneous Mixture Model for Semi-supervised Clustering of Heart Enhancers. Bioinformatics 2019 Feb 7
Bioinformatics link PDF Mirror PubMed Abstract Article
Regulatory networks Transcription factors Genomics Machine Learning

Microscope images are big data

Lu et al. 2016
Handfield et al. 2015
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Automated microscopy has made it possible to measuring protein abundance and subcellular localization in millions of single cells. We are developing computational tools to extract basic biology from huge collections of microscope images without have to look at each one.

LATEST PAPERS:

Moses AM, Lu AX, Lu AX, Ghassemi M Transfer Learning vs. Batch Effects: what can we expect from neural networks in computational biology? 14th Machine Learning in Computational Biology (MLCB 2019)
MLCB link PDF Mirror review
Deep Learning Covariate shift Image analysis transcription factor binding
Lu AX, Lu AX, Schormann W, Ghassemi M, Andrews DW, Moses AM The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers Advances in Neural Information Processing Systems 32 (NeurIPS 2019)
NeurIPS link PDF Mirror Book Chapter
Deep Learning Covariate shift Image analysis Subcellular localization

Molecular Evolution of Disordered Regions

Zarin et al. 2017
Zarin et al. 2017
Zarin et al. 2017
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Intrinsically Disordered Regions (or IDRs) are enigmatic protein regions that are involved in a wide variety of biological processes. Although they are widespread, they usually show little evolutionary conservation. Is this rapid evolution a sign that they are just "junk" protein, or do they facilitate evolutionary diversity? This question is also of medical relevance: when we find mutations in patients' IDRs we currently cannot tell what impact (if any) they are having.

LATEST PAPERS:

Pritišanac I, Zarin T, Forman-Kay JD, Moses AM Whence Blobs? Phylogenetics of functional protein condensates Biochem Soc Trans. 2020 Sep 28
Biochem Soc Trans. Link PDF Mirror PubMed AbstractReview
Molecular Evolution Intrinsically disordered regions Phase separation Protein Condensation
Iserman C, Desroches Altamirano C, Jegers C, Friedrich U, Zarin T, Fritsch AW, Mittasch M, Domingues A, Hersemann L, Jahnel M, Richter D, Guenther UP, Hentze MW, Moses AM, Hyman AA, Kramer G, Kreysing M, Franzmann TM, Alberti S Condensation of Ded1p Promotes a Translational Switch from Housekeeping to Stress Protein Production Cell. 2020 May 14;181(4):818-831.e19.
Cell Press Link PDF Mirror PubMed AbstractArticle
Molecular Evolution Intrinsically disordered regions Phase separation Protein Condensation

Beautiful bioinformatics for genomics and proteomics

Davey et al. 2015
Lai et al. 2012
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Complete sequencing of genomes is now routine, and yields thousands of genes and proteins, and information about the genetic differences in populations. All of this data needs to be organized and analyzed: bioinformatics!

LATEST PAPERS:

Michowski W, Chick JM, Chu C, Kolodziejczyk A, Wang Y, Suski JM, Abraham B, Anders L, Day D, Dunkl LM, Li Cheong Man M, Zhang T, Laphanuwat P, Bacon NA, Liu L, Fassl A, Sharma S, Otto T, Jecrois E, Han R, Sweeney KE, Marro S, Wernig M, Geng Y, Moses A, Li C, Gygi SP, Young RA, Sicinski P Cdk1 Controls Global Epigenetic Landscape in Embryonic Stem Cells Mol Cell. 2020 May 7;78(3):459-476.e13
Cell Press Link PDF Mirror PubMed AbstractArticle
kinase Regulatory Networks transcription factor Proteomics
Mehdi TF, Singh G, Mitchell JA, Moses AM. Variational Infinite Heterogeneous Mixture Model for Semi-supervised Clustering of Heart Enhancers. Bioinformatics 2019 Feb 7
Bioinformatics link PDF Mirror PubMed Abstract Article
Regulatory networks Transcription factors Genomics Machine Learning