doi.bio/debora_s_marks

Debora S. Marks

Overview

Debora S. Marks is a researcher in computational biology and a Professor of Systems Biology at Harvard Medical School. Her research uses computational approaches to address a variety of biological problems. She is best known for her work on protein structure prediction.

Education

After an undergraduate degree in medicine, Marks worked in the pharmaceutical industry. She returned to academia later in life, obtaining a mathematics degree from the University of Manchester. She then pursued a PhD in biology at Humboldt University of Berlin, which she completed in 2010.

Research

Marks' research focuses on developing computational methods to interpret genetic variation and its impact on biomedical research. She is particularly interested in the following areas:

• Protein structure prediction
• RNA structure and function prediction
• Machine learning and statistical inference
• Neurodegenerative diseases
• Antibiotic resistance
• Vaccine design
• Immunogenomics
• Molecular design

Notable Contributions

• Discovered that transfection of microRNAs into cells increases the expression of some genes due to competition for cellular machinery.
• Developed a method for protein structure prediction using an approach from statistical physics, which has been extensively used by other researchers.
• Developed machine learning models to predict the effects of mutations and accelerate the diagnosis and treatment of genetic diseases.
• Contributed to the PopEVE project on population genetics.

Awards and Recognition

• Overton Prize by the International Society for Computational Biology (2016)
• Ben Barres Early Career Award by the Chan Zuckerberg Initiative (2018)
• Elected as a Fellow of the International Society for Computational Biology (2022)

Publications

Marks has published extensively in the field of computational biology, with a focus on machine learning and genomics. Some of her notable publications include:

• "Combining Family-specific and Family-agnostic Models of Protein Sequences for Improved Fitness Prediction"
• "Large-scale discovery of protein interactions at residue resolution using co-evolution calculated from genomic sequences"
• "High-content screening of coronavirus genes for innate immune suppression reveals enhanced potency of SARS-CoV-2 proteins"
• "Large-scale clinical interpretation of genetic variants using evolutionary data and deep learning"
• "CellBox: Interpretable Machine Learning for Perturbation Biology with Application to the Design of Cancer Combination Therapy"

Affiliations

• Harvard Medical School
• Broad Institute of Harvard and MIT

- Dana-Farber Cancer Institute

Debora S. Marks

Overview

Debora S. Marks is a researcher in computational biology and a Professor of Systems Biology at Harvard Medical School. Her research uses computational approaches to address a variety of biological problems. She is best known for her work on protein structure prediction.

Education

After an undergraduate degree in medicine, Marks worked in the pharmaceutical industry. She returned to academia later in life, obtaining a mathematics degree from the University of Manchester. She became interested in microRNAs in the early 2000s, and her work in this area formed the basis of her PhD thesis, which she submitted to Humboldt University of Berlin in 2010.

Career

Marks is currently a Professor in the Department of Systems Biology at Harvard Medical School. She runs the Marks Lab, a new interdisciplinary lab dedicated to developing rigorous computational approaches to critical challenges in biomedical research, particularly on the interpretation of genetic variation and its impact on basic science and clinical medicine.

Research

Marks' research focuses on developing novel statistical methods that combine theory and computation to extract useful information from biological data. She has worked on problems in four interrelated areas of biology:

• Three-dimensional structure and dynamics of proteins and RNA
• Effects of mutations and fitness, especially for viral evolution
• Immunogenomics
• Biotherapeutic molecular design

She has adapted and developed deep neural methods, particularly unsupervised generative modelling, for application to biological sequences. She is also interested in machine learning, genomics, and drug design.

Awards and Honours

• 2016: Overton Prize by the International Society for Computational Biology
• 2018: Ben Barres Early Career Award by the Chan Zuckerberg Initiative as part of the Neurodegeneration Challenge Network
• 2022: Elected as a Fellow of the International Society for Computational Biology

Selected Publications

• Stiffler, M. A. (n.d.). Protein structure from experimental evolution.
• TranceptEVE: Combining Family-specific and Family-agnostic Models of Protein Sequences for Improved Fitness Prediction.
• Integrated genomic, phenomic, functional and structural mapping of variants in thyroid hormone transporter MCT8.
• scPerturb: Information Resource for Harmonized Single-Cell Perturbation Data.
• Dormant spores sense amino acids through the B subunits of their germination receptors.
• Large-scale discovery of protein interactions at residue resolution using co-evolution calculated from genomic sequences.
• High-content screening of coronavirus genes for innate immune suppression reveals enhanced potency of SARS-CoV-2 proteins.
• Large-scale clinical interpretation of genetic variants using evolutionary data and deep learning.
• CellBox: Interpretable Machine Learning for Perturbation Biology with Application to the Design of Cancer Combination Therapy.
• Rapid generation of potent antibodies by autonomous hypermutation in yeast.
• Multiplexed measurement of variant abundance and activity reveals VKOR topology, active site and human variant impact.
• Multiplexed measurement of variant abundance and activity reveals VKOR topology, active site and human variant impact.
• Abstract 2102: Interpretable machine learning for perturbation biology.
• Generative probabilistic biological sequence models that account for mutational variability.
• Structural coordination of polymerization and crosslinking by a SEDS–bPBP peptidoglycan synthase complex.

Google Scholar Profile

Debora S Marks)

Google Scholar

Debora Marks Systems Biology, Harvard Medical School, Broad Institute of Harvard and MIT https://marks.hms.harvard.edu/ Human microRNA targets B John, AJ Enright, A Aravin, T Tuschl, C Sander, DS Marks PLoS biology 2 (11), e363, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:u5HHmVD_uO8C Cited by: 4513

MicroRNA targets in Drosophila AJ Enright, B John, U Gaul, T Tuschl, C Sander, DS Marks Genome biology 5 (1), 1-1, 2003 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:u-x6o8ySG0sC Cited by: 3852

The microRNA. org resource: targets and expression D Betel, M Wilson, A Gabow, DS Marks, C Sander Nucleic acids research 36 (suppl1), D149-D153, 2008 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationfor_view=qFmoeNkAAAAJ:2osOgNQ5qMEC Cited by: 2972

Identification of virus-encoded microRNAs S Pfeffer, M Zavolan, FA Grässer, M Chien, JJ Russo, J Ju, B John, … Science 304 (5671), 734-736, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:d1gkVwhDpl0C Cited by: 2095

Direct-coupling analysis of residue coevolution captures native contacts across many protein families F Morcos, A Pagnani, B Lunt, A Bertolino, DS Marks, C Sander, … Proceedings of the National Academy of Sciences 108 (49), E1293-E1301, 2011 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:8k81kl-MbHgC Cited by: 1512

The small RNA profile during Drosophila melanogaster development AA Aravin, M Lagos-Quintana, A Yalcin, M Zavolan, D Marks, B Snyder, … Developmental cell 5 (2), 337-350, 2003 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:9yKSN-GCB0IC Cited by: 1283

Protein 3D structure computed from evolutionary sequence variation DS Marks, LJ Colwell, R Sheridan, TA Hopf, A Pagnani, R Zecchina, … PloS one 6 (12), e28766, 2011 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:kNdYIx-mwKoC Cited by: 1234

miR-122, a mammalian liver-specific microRNA, is processed from hcr mRNA and maydownregulate the high affinity cationic amino acid transporter CAT-1 J Chang, E Nicolas, D Marks, C Sander, A Lerro, MA Buendia, C Xu, … RNA biology 1 (2), 106-113, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:qjMakFHDy7sC Cited by: 1046

Protein structure prediction from sequence variation DS Marks, TA Hopf, C Sander Nature biotechnology 30 (11), 1072-1080, 2012 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:IWHjjKOFINEC Cited by: 704

miRcode: a map of putative microRNA target sites in the long non-coding transcriptome A Jeggari, DS Marks, E Larsson Bioinformatics 28 (15), 2062-2063, 2012 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:7PzlFSSx8tAC Cited by: 679

Transfection of small RNAs globally perturbs gene regulation by endogenous microRNAs AA Khan, D Betel, ML Miller, C Sander, CS Leslie, DS Marks Nature biotechnology 27 (6), 549-555, 2009 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:Y0pCki6q_DkC Cited by: 656

Mutation effects predicted from sequence co-variation TA Hopf, JB Ingraham, FJ Poelwijk, CPI Schärfe, M Springer, C Sander, … Nature biotechnology 35 (2), 128-135, 2017 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:EUQCXRtRnyEC Cited by: 620

Three-dimensional structures of membrane proteins from genomic sequencing TA Hopf, LJ Colwell, R Sheridan, B Rost, C Sander, DS Marks Cell 149 (7), 1607-1621, 2012 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:dhFuZR0502QC Cited by: 591

MicroRNA profiling of the murine hematopoietic system S Monticelli, KM Ansel, C Xiao, ND Socci, AM Krichevsky, TH Thai, … Genome biology 6, 1-15, 2005 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:UeHWp8X0CEIC Cited by: 562

Deep generative models of genetic variation capture the effects of mutations AJ Riesselman, JB Ingraham, DS Marks Nature methods 15 (10), 816-822, 2018 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:VOx2b1Wkg3QC Cited by: 533

Sequence co-evolution gives 3D contacts and structures of protein complexes TA Hopf, CPI Schärfe, JP Rodrigues, AG Green, O Kohlbacher, C Sander, … elife 3, e03430, 2014 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:iH-uZ7U-co4C Cited by: 531

The developmental miRNA profiles of zebrafish as determined by small RNA cloning PY Chen, H Manninga, K Slanchev, M Chien, JJ Russo, J Ju, R Sheridan, … Genes & development 19 (11), 1288-1293, 2005 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:zYLM7Y9cAGgC Cited by: 438

Disease variant prediction with deep generative models of evolutionary data J Frazer, P Notin, M Dias, A Gomez, JK Min, K Brock, Y Gal, DS Marks Nature 599 (7883), 91-95, 2021 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:2KloaMYe4IUC Cited by: 435

MicroRNA control of protein expression noise JM Schmiedel, SL Klemm, Y Zheng, A Sahay, N Blüthgen, DS Marks, … Science 348 (6230), 128-132, 2015 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:GnPB-g6toBAC Cited by: 424

Scientific discovery in the age of artificial intelligence H Wang, T Fu, Y Du, W Gao, K Huang, Z Liu, P Chandak, S Liu, … Nature 620 (7972), 47-60, 2023 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:S16KYo8Pm5AC Cited by: 422

Co-authors

Chris Sander 4R7_wW8AAAAJ

Thomas A. Hopf dK2eepUAAAAJ

John Ingraham qBarioAAAAAJ

Anton Enright kucwB9kAAAAJ

Anna G. Green o9rcausAAAAJ

Charlotta Scharfe fCmpyIYAAAAJ

Riccardo Zecchina fNOReswAAAAJ

Doron Betel G5MjfRMAAAAJ

Christina Leslie e25-lgUAAAAJ

Andrea Pagnani EWJYRncAAAAJ

James J. Russo UTY6T2MAAAAJ

Martin Weigt HU1K_zsAAAAJ

Bryan J. Lunt XV30l4MAAAAJ

Erik Larsson Lekholm m1lhgKgAAAAJ

Sébastien Pfeffer zjm3WT0AAAAJ

Burkhard Rost BP3ofxcAAAAJ

Martin L Miller nuyBlicAAAAJ

Anders Jacobsen Skanderup r06O54MAAAAJ

Aaron Arvey W4isOSEAAAAJ

Kenneth S. Kosik 4jg-_CUAAAAJ

Google Scholar

Debora Marks Systems Biology, Harvard Medical School, Broad Institute of Harvard and MIT https://marks.hms.harvard.edu/ Human microRNA targets B John, AJ Enright, A Aravin, T Tuschl, C Sander, DS Marks PLoS biology 2 (11), e363, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:u5HHmVD_uO8C Cited by: 4513

MicroRNA targets in Drosophila AJ Enright, B John, U Gaul, T Tuschl, C Sander, DS Marks Genome biology 5 (1), 1-1, 2003 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:u-x6o8ySG0sC Cited by: 3852

The microRNA. org resource: targets and expression D Betel, M Wilson, A Gabow, DS Marks, C Sander Nucleic acids research 36 (suppl1), D149-D153, 2008 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationfor_view=qFmoeNkAAAAJ:2osOgNQ5qMEC Cited by: 2972

Identification of virus-encoded microRNAs S Pfeffer, M Zavolan, FA Grässer, M Chien, JJ Russo, J Ju, B John, … Science 304 (5671), 734-736, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:d1gkVwhDpl0C Cited by: 2095

Direct-coupling analysis of residue coevolution captures native contacts across many protein families F Morcos, A Pagnani, B Lunt, A Bertolino, DS Marks, C Sander, … Proceedings of the National Academy of Sciences 108 (49), E1293-E1301, 2011 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:8k81kl-MbHgC Cited by: 1512

The small RNA profile during Drosophila melanogaster development AA Aravin, M Lagos-Quintana, A Yalcin, M Zavolan, D Marks, B Snyder, … Developmental cell 5 (2), 337-350, 2003 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:9yKSN-GCB0IC Cited by: 1283

Protein 3D structure computed from evolutionary sequence variation DS Marks, LJ Colwell, R Sheridan, TA Hopf, A Pagnani, R Zecchina, … PloS one 6 (12), e28766, 2011 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:kNdYIx-mwKoC Cited by: 1234

miR-122, a mammalian liver-specific microRNA, is processed from hcr mRNA and maydownregulate the high affinity cationic amino acid transporter CAT-1 J Chang, E Nicolas, D Marks, C Sander, A Lerro, MA Buendia, C Xu, … RNA biology 1 (2), 106-113, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:qjMakFHDy7sC Cited by: 1046

Protein structure prediction from sequence variation DS Marks, TA Hopf, C Sander Nature biotechnology 30 (11), 1072-1080, 2012 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:IWHjjKOFINEC Cited by: 704

miRcode: a map of putative microRNA target sites in the long non-coding transcriptome A Jeggari, DS Marks, E Larsson Bioinformatics 28 (15), 2062-2063, 2012 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:7PzlFSSx8tAC Cited by: 679

Transfection of small RNAs globally perturbs gene regulation by endogenous microRNAs AA Khan, D Betel, ML Miller, C Sander, CS Leslie, DS Marks Nature biotechnology 27 (6), 549-555, 2009 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:Y0pCki6q_DkC Cited by: 656

Mutation effects predicted from sequence co-variation TA Hopf, JB Ingraham, FJ Poelwijk, CPI Schärfe, M Springer, C Sander, … Nature biotechnology 35 (2), 128-135, 2017 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:EUQCXRtRnyEC Cited by: 620

Three-dimensional structures of membrane proteins from genomic sequencing TA Hopf, LJ Colwell, R Sheridan, B Rost, C Sander, DS Marks Cell 149 (7), 1607-1621, 2012 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:dhFuZR0502QC Cited by: 591

MicroRNA profiling of the murine hematopoietic system S Monticelli, KM Ansel, C Xiao, ND Socci, AM Krichevsky, TH Thai, … Genome biology 6, 1-15, 2005 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:UeHWp8X0CEIC Cited by: 562

Deep generative models of genetic variation capture the effects of mutations AJ Riesselman, JB Ingraham, DS Marks Nature methods 15 (10), 816-822, 2018 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:VOx2b1Wkg3QC Cited by: 533

Sequence co-evolution gives 3D contacts and structures of protein complexes TA Hopf, CPI Schärfe, JP Rodrigues, AG Green, O Kohlbacher, C Sander, … elife 3, e03430, 2014 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:iH-uZ7U-co4C Cited by: 531

The developmental miRNA profiles of zebrafish as determined by small RNA cloning PY Chen, H Manninga, K Slanchev, M Chien, JJ Russo, J Ju, R Sheridan, … Genes & development 19 (11), 1288-1293, 2005 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:zYLM7Y9cAGgC Cited by: 438

Disease variant prediction with deep generative models of evolutionary data J Frazer, P Notin, M Dias, A Gomez, JK Min, K Brock, Y Gal, DS Marks Nature 599 (7883), 91-95, 2021 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:2KloaMYe4IUC Cited by: 435

MicroRNA control of protein expression noise JM Schmiedel, SL Klemm, Y Zheng, A Sahay, N Blüthgen, DS Marks, … Science 348 (6230), 128-132, 2015 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:GnPB-g6toBAC Cited by: 424

Scientific discovery in the age of artificial intelligence H Wang, T Fu, Y Du, W Gao, K Huang, Z Liu, P Chandak, S Liu, … Nature 620 (7972), 47-60, 2023 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:S16KYo8Pm5AC Cited by: 422

Co-authors

Chris Sander googlescholarauthorid:4R7wW8AAAAJ

Thomas A. Hopf googlescholarauthor_id:dK2eepUAAAAJ

John Ingraham googlescholarauthor_id:qBarioAAAAAJ

Anton Enright googlescholarauthor_id:kucwB9kAAAAJ

Anna G. Green googlescholarauthor_id:o9rcausAAAAJ

Charlotta Scharfe googlescholarauthor_id:fCmpyIYAAAAJ

Riccardo Zecchina googlescholarauthor_id:fNOReswAAAAJ

Doron Betel googlescholarauthor_id:G5MjfRMAAAAJ

Christina Leslie googlescholarauthor_id:e25-lgUAAAAJ

Andrea Pagnani googlescholarauthor_id:EWJYRncAAAAJ

James J. Russo googlescholarauthor_id:UTY6T2MAAAAJ

Martin Weigt googlescholarauthorid:HU1KzsAAAAJ

Bryan J. Lunt googlescholarauthor_id:XV30l4MAAAAJ

Erik Larsson Lekholm googlescholarauthor_id:m1lhgKgAAAAJ

Sébastien Pfeffer googlescholarauthor_id:zjm3WT0AAAAJ

Burkhard Rost googlescholarauthor_id:BP3ofxcAAAAJ

Martin L Miller googlescholarauthor_id:nuyBlicAAAAJ

Anders Jacobsen Skanderup googlescholarauthor_id:r06O54MAAAAJ

Aaron Arvey googlescholarauthor_id:W4isOSEAAAAJ

Kenneth S. Kosik googlescholarauthorid:4jg-CUAAAAJ

Google Scholar

Debora Marks Systems Biology, Harvard Medical School, Broad Institute of Harvard and MIT https://marks.hms.harvard.edu/ Human microRNA targets B John, AJ Enright, A Aravin, T Tuschl, C Sander, DS Marks PLoS biology 2 (11), e363, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:u5HHmVD_uO8C Cited by: 4513

MicroRNA targets in Drosophila AJ Enright, B John, U Gaul, T Tuschl, C Sander, DS Marks Genome biology 5 (1), 1-1, 2003 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:u-x6o8ySG0sC Cited by: 3852

The microRNA. org resource: targets and expression D Betel, M Wilson, A Gabow, DS Marks, C Sander Nucleic acids research 36 (suppl1), D149-D153, 2008 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationfor_view=qFmoeNkAAAAJ:2osOgNQ5qMEC Cited by: 2972

Identification of virus-encoded microRNAs S Pfeffer, M Zavolan, FA Grässer, M Chien, JJ Russo, J Ju, B John, … Science 304 (5671), 734-736, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:d1gkVwhDpl0C Cited by: 2095

Direct-coupling analysis of residue coevolution captures native contacts across many protein families F Morcos, A Pagnani, B Lunt, A Bertolino, DS Marks, C Sander, … Proceedings of the National Academy of Sciences 108 (49), E1293-E1301, 2011 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:8k81kl-MbHgC Cited by: 1512

The small RNA profile during Drosophila melanogaster development AA Aravin, M Lagos-Quintana, A Yalcin, M Zavolan, D Marks, B Snyder, … Developmental cell 5 (2), 337-350, 2003 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:9yKSN-GCB0IC Cited by: 1283

Protein 3D structure computed from evolutionary sequence variation DS Marks, LJ Colwell, R Sheridan, TA Hopf, A Pagnani, R Zecchina, … PloS one 6 (12), e28766, 2011 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:kNdYIx-mwKoC Cited by: 1234

miR-122, a mammalian liver-specific microRNA, is processed from hcr mRNA and maydownregulate the high affinity cationic amino acid transporter CAT-1 J Chang, E Nicolas, D Marks, C Sander, A Lerro, MA Buendia, C Xu, … RNA biology 1 (2), 106-113, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:qjMakFHDy7sC Cited by: 1046

Protein structure prediction from sequence variation DS Marks, TA Hopf, C Sander Nature biotechnology 30 (11), 1072-1080, 2012 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:IWHjjKOFINEC Cited by: 704

miRcode: a map of putative microRNA target sites in the long non-coding transcriptome A Jeggari, DS Marks, E Larsson Bioinformatics 28 (15), 2062-2063, 2012 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:7PzlFSSx8tAC Cited by: 679

Transfection of small RNAs globally perturbs gene regulation by endogenous microRNAs AA Khan, D Betel, ML Miller, C Sander, CS Leslie, DS Marks Nature biotechnology 27 (6), 549-555, 2009 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:Y0pCki6q_DkC Cited by: 656

Mutation effects predicted from sequence co-variation TA Hopf, JB Ingraham, FJ Poelwijk, CPI Schärfe, M Springer, C Sander, … Nature biotechnology 35 (2), 128-135, 2017 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:EUQCXRtRnyEC Cited by: 620

Three-dimensional structures of membrane proteins from genomic sequencing TA Hopf, LJ Colwell, R Sheridan, B Rost, C Sander, DS Marks Cell 149 (7), 1607-1621, 2012 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:dhFuZR0502QC Cited by: 591

MicroRNA profiling of the murine hematopoietic system S Monticelli, KM Ansel, C Xiao, ND Socci, AM Krichevsky, TH Thai, … Genome biology 6, 1-15, 2005 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:UeHWp8X0CEIC Cited by: 562

Deep generative models of genetic variation capture the effects of mutations AJ Riesselman, JB Ingraham, DS Marks Nature methods 15 (10), 816-822, 2018 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:VOx2b1Wkg3QC Cited by: 533

Sequence co-evolution gives 3D contacts and structures of protein complexes TA Hopf, CPI Schärfe, JP Rodrigues, AG Green, O Kohlbacher, C Sander, … elife 3, e03430, 2014 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:iH-uZ7U-co4C Cited by: 531

The developmental miRNA profiles of zebrafish as determined by small RNA cloning PY Chen, H Manninga, K Slanchev, M Chien, JJ Russo, J Ju, R Sheridan, … Genes & development 19 (11), 1288-1293, 2005 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:zYLM7Y9cAGgC Cited by: 438

Disease variant prediction with deep generative models of evolutionary data J Frazer, P Notin, M Dias, A Gomez, JK Min, K Brock, Y Gal, DS Marks Nature 599 (7883), 91-95, 2021 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:2KloaMYe4IUC Cited by: 435

MicroRNA control of protein expression noise JM Schmiedel, SL Klemm, Y Zheng, A Sahay, N Blüthgen, DS Marks, … Science 348 (6230), 128-132, 2015 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:GnPB-g6toBAC Cited by: 424

Scientific discovery in the age of artificial intelligence H Wang, T Fu, Y Du, W Gao, K Huang, Z Liu, P Chandak, S Liu, … Nature 620 (7972), 47-60, 2023 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:S16KYo8Pm5AC Cited by: 422

Co-authors

Chris Sander googlescholarauthorid:[chrissander.md][4R7_wW8AAAAJ]

Thomas A. Hopf googlescholarauthorid:[thomasa._hopf.md][dK2eepUAAAAJ]

John Ingraham googlescholarauthorid:[johningraham.md][qBarioAAAAAJ]

Anton Enright googlescholarauthorid:[antonenright.md][kucwB9kAAAAJ]

Anna G. Green googlescholarauthorid:[annag._green.md][o9rcausAAAAJ]

Charlotta Scharfe googlescholarauthorid:[charlottascharfe.md][fCmpyIYAAAAJ]

Riccardo Zecchina googlescholarauthorid:[riccardozecchina.md][fNOReswAAAAJ]

Doron Betel googlescholarauthorid:[doronbetel.md][G5MjfRMAAAAJ]

Christina Leslie googlescholarauthorid:[christinaleslie.md][e25-lgUAAAAJ]

Andrea Pagnani googlescholarauthorid:[andreapagnani.md][EWJYRncAAAAJ]

James J. Russo googlescholarauthorid:[jamesj._russo.md][UTY6T2MAAAAJ]

Martin Weigt googlescholarauthorid:[martinweigt.md][HU1K_zsAAAAJ]

Bryan J. Lunt googlescholarauthorid:[bryanj._lunt.md][XV30l4MAAAAJ]

Erik Larsson Lekholm googlescholarauthorid:[eriklarsson_lekholm.md][m1lhgKgAAAAJ]

Sébastien Pfeffer googlescholarauthorid:[sébastienpfeffer.md][zjm3WT0AAAAJ]

Burkhard Rost googlescholarauthorid:[burkhardrost.md][BP3ofxcAAAAJ]

Martin L Miller googlescholarauthorid:[martinl_miller.md][nuyBlicAAAAJ]

Anders Jacobsen Skanderup googlescholarauthorid:[andersjacobsen_skanderup.md][r06O54MAAAAJ]

Aaron Arvey googlescholarauthorid:[aaronarvey.md][W4isOSEAAAAJ]

Kenneth S. Kosik googlescholarauthorid:[kenneths.kosik.md][4jg-CUAAAAJ]

Google Scholar

Debora Marks Systems Biology, Harvard Medical School, Broad Institute of Harvard and MIT https://marks.hms.harvard.edu/ Human microRNA targets B John, AJ Enright, A Aravin, T Tuschl, C Sander, DS Marks PLoS biology 2 (11), e363, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:u5HHmVD_uO8C Cited by: 4513

MicroRNA targets in Drosophila AJ Enright, B John, U Gaul, T Tuschl, C Sander, DS Marks Genome biology 5 (1), 1-1, 2003 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:u-x6o8ySG0sC Cited by: 3852

The microRNA. org resource: targets and expression D Betel, M Wilson, A Gabow, DS Marks, C Sander Nucleic acids research 36 (suppl1), D149-D153, 2008 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationfor_view=qFmoeNkAAAAJ:2osOgNQ5qMEC Cited by: 2972

Identification of virus-encoded microRNAs S Pfeffer, M Zavolan, FA Grässer, M Chien, JJ Russo, J Ju, B John, … Science 304 (5671), 734-736, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:d1gkVwhDpl0C Cited by: 2095

Direct-coupling analysis of residue coevolution captures native contacts across many protein families F Morcos, A Pagnani, B Lunt, A Bertolino, DS Marks, C Sander, … Proceedings of the National Academy of Sciences 108 (49), E1293-E1301, 2011 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:8k81kl-MbHgC Cited by: 1512

The small RNA profile during Drosophila melanogaster development AA Aravin, M Lagos-Quintana, A Yalcin, M Zavolan, D Marks, B Snyder, … Developmental cell 5 (2), 337-350, 2003 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:9yKSN-GCB0IC Cited by: 1283

Protein 3D structure computed from evolutionary sequence variation DS Marks, LJ Colwell, R Sheridan, TA Hopf, A Pagnani, R Zecchina, … PloS one 6 (12), e28766, 2011 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:kNdYIx-mwKoC Cited by: 1234

miR-122, a mammalian liver-specific microRNA, is processed from hcr mRNA and maydownregulate the high affinity cationic amino acid transporter CAT-1 J Chang, E Nicolas, D Marks, C Sander, A Lerro, MA Buendia, C Xu, … RNA biology 1 (2), 106-113, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:qjMakFHDy7sC Cited by: 1046

Protein structure prediction from sequence variation DS Marks, TA Hopf, C Sander Nature biotechnology 30 (11), 1072-1080, 2012 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:IWHjjKOFINEC Cited by: 704

miRcode: a map of putative microRNA target sites in the long non-coding transcriptome A Jeggari, DS Marks, E Larsson Bioinformatics 28 (15), 2062-2063, 2012 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:7PzlFSSx8tAC Cited by: 679

Transfection of small RNAs globally perturbs gene regulation by endogenous microRNAs AA Khan, D Betel, ML Miller, C Sander, CS Leslie, DS Marks Nature biotechnology 27 (6), 549-555, 2009 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:Y0pCki6q_DkC Cited by: 656

Mutation effects predicted from sequence co-variation TA Hopf, JB Ingraham, FJ Poelwijk, CPI Schärfe, M Springer, C Sander, … Nature biotechnology 35 (2), 128-135, 2017 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:EUQCXRtRnyEC Cited by: 620

Three-dimensional structures of membrane proteins from genomic sequencing TA Hopf, LJ Colwell, R Sheridan, B Rost, C Sander, DS Marks Cell 149 (7), 1607-1621, 2012 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:dhFuZR0502QC Cited by: 591

MicroRNA profiling of the murine hematopoietic system S Monticelli, KM Ansel, C Xiao, ND Socci, AM Krichevsky, TH Thai, … Genome biology 6, 1-15, 2005 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:UeHWp8X0CEIC Cited by: 562

Deep generative models of genetic variation capture the effects of mutations AJ Riesselman, JB Ingraham, DS Marks Nature methods 15 (10), 816-822, 2018 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:VOx2b1Wkg3QC Cited by: 533

Sequence co-evolution gives 3D contacts and structures of protein complexes TA Hopf, CPI Schärfe, JP Rodrigues, AG Green, O Kohlbacher, C Sander, … elife 3, e03430, 2014 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:iH-uZ7U-co4C Cited by: 531

The developmental miRNA profiles of zebrafish as determined by small RNA cloning PY Chen, H Manninga, K Slanchev, M Chien, JJ Russo, J Ju, R Sheridan, … Genes & development 19 (11), 1288-1293, 2005 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:zYLM7Y9cAGgC Cited by: 438

Disease variant prediction with deep generative models of evolutionary data J Frazer, P Notin, M Dias, A Gomez, JK Min, K Brock, Y Gal, DS Marks Nature 599 (7883), 91-95, 2021 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:2KloaMYe4IUC Cited by: 435

MicroRNA control of protein expression noise JM Schmiedel, SL Klemm, Y Zheng, A Sahay, N Blüthgen, DS Marks, … Science 348 (6230), 128-132, 2015 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:GnPB-g6toBAC Cited by: 424

Scientific discovery in the age of artificial intelligence H Wang, T Fu, Y Du, W Gao, K Huang, Z Liu, P Chandak, S Liu, … Nature 620 (7972), 47-60, 2023 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:S16KYo8Pm5AC Cited by: 422

Co-authors

Chris Sander googlescholarauthorid chrissander.md:4R7_wW8AAAAJ

Thomas A. Hopf googlescholarauthorid thomasa._hopf.md:dK2eepUAAAAJ

John Ingraham googlescholarauthorid johningraham.md:qBarioAAAAAJ

Anton Enright googlescholarauthorid antonenright.md:kucwB9kAAAAJ

Anna G. Green googlescholarauthorid annag._green.md:o9rcausAAAAJ

Charlotta Scharfe googlescholarauthorid charlottascharfe.md:fCmpyIYAAAAJ

Riccardo Zecchina googlescholarauthorid riccardozecchina.md:fNOReswAAAAJ

Doron Betel googlescholarauthorid doronbetel.md:G5MjfRMAAAAJ

Christina Leslie googlescholarauthorid christinaleslie.md:e25-lgUAAAAJ

Andrea Pagnani googlescholarauthorid andreapagnani.md:EWJYRncAAAAJ

James J. Russo googlescholarauthorid jamesj._russo.md:UTY6T2MAAAAJ

Martin Weigt googlescholarauthorid martinweigt.md:HU1K_zsAAAAJ

Bryan J. Lunt googlescholarauthorid bryanj._lunt.md:XV30l4MAAAAJ

Erik Larsson Lekholm googlescholarauthorid eriklarsson_lekholm.md:m1lhgKgAAAAJ

Sébastien Pfeffer googlescholarauthorid sébastienpfeffer.md:zjm3WT0AAAAJ

Burkhard Rost googlescholarauthorid burkhardrost.md:BP3ofxcAAAAJ

Martin L Miller googlescholarauthorid martinl_miller.md:nuyBlicAAAAJ

Anders Jacobsen Skanderup googlescholarauthorid andersjacobsen_skanderup.md:r06O54MAAAAJ

Aaron Arvey googlescholarauthorid aaronarvey.md:W4isOSEAAAAJ

Kenneth S. Kosik googlescholarauthorid kenneths.kosik.md:4jg-CUAAAAJ

Google Scholar

Debora Marks

Systems Biology, Harvard Medical School, Broad Institute of Harvard and MIT

https://marks.hms.harvard.edu/

Human microRNA targets B John, AJ Enright, A Aravin, T Tuschl, C Sander, DS Marks PLoS biology 2 (11), e363, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:u5HHmVD_uO8C

MicroRNA targets in Drosophila AJ Enright, B John, U Gaul, T Tuschl, C Sander, DS Marks Genome biology 5 (1), 1-1, 2003 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:u-x6o8ySG0sC

The microRNA. org resource: targets and expression D Betel, M Wilson, A Gabow, DS Marks, C Sander Nucleic acids research 36 (suppl1), D149-D153, 2008 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationfor_view=qFmoeNkAAAAJ:2osOgNQ5qMEC

Identification of virus-encoded microRNAs S Pfeffer, M Zavolan, FA Grässer, M Chien, JJ Russo, J Ju, B John, … Science 304 (5671), 734-736, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:d1gkVwhDpl0C

Direct-coupling analysis of residue coevolution captures native contacts across many protein families F Morcos, A Pagnani, B Lunt, A Bertolino, DS Marks, C Sander, … Proceedings of the National Academy of Sciences 108 (49), E1293-E1301, 2011 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:8k81kl-MbHgC

The small RNA profile during Drosophila melanogaster development AA Aravin, M Lagos-Quintana, A Yalcin, M Zavolan, D Marks, B Snyder, … Developmental cell 5 (2), 337-350, 2003 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:9yKSN-GCB0IC

Protein 3D structure computed from evolutionary sequence variation DS Marks, LJ Colwell, R Sheridan, TA Hopf, A Pagnani, R Zecchina, … PloS one 6 (12), e28766, 2011 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:kNdYIx-mwKoC

miR-122, a mammalian liver-specific microRNA, is processed from hcr mRNA and maydownregulate the high affinity cationic amino acid transporter CAT-1 J Chang, E Nicolas, D Marks, C Sander, A Lerro, MA Buendia, C Xu, … RNA biology 1 (2), 106-113, 2004 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:qjMakFHDy7sC

Protein structure prediction from sequence variation DS Marks, TA Hopf, C Sander Nature biotechnology 30 (11), 1072-1080, 2012 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:IWHjjKOFINEC

miRcode: a map of putative microRNA target sites in the long non-coding transcriptome A Jeggari, DS Marks, E Larsson Bioinformatics 28 (15), 2062-2063, 2012 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:7PzlFSSx8tAC

Transfection of small RNAs globally perturbs gene regulation by endogenous microRNAs AA Khan, D Betel, ML Miller, C Sander, CS Leslie, DS Marks Nature biotechnology 27 (6), 549-555, 2009 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:Y0pCki6q_DkC

Mutation effects predicted from sequence co-variation TA Hopf, JB Ingraham, FJ Poelwijk, CPI Schärfe, M Springer, C Sander, … Nature biotechnology 35 (2), 128-135, 2017 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:EUQCXRtRnyEC

Three-dimensional structures of membrane proteins from genomic sequencing TA Hopf, LJ Colwell, R Sheridan, B Rost, C Sander, DS Marks Cell 149 (7), 1607-1621, 2012 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:dhFuZR0502QC

MicroRNA profiling of the murine hematopoietic system S Monticelli, KM Ansel, C Xiao, ND Socci, AM Krichevsky, TH Thai, … Genome biology 6, 1-15, 2005 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:UeHWp8X0CEIC

Deep generative models of genetic variation capture the effects of mutations AJ Riesselman, JB Ingraham, DS Marks Nature methods 15 (10), 816-822, 2018 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:VOx2b1Wkg3QC

Sequence co-evolution gives 3D contacts and structures of protein complexes TA Hopf, CPI Schärfe, JP Rodrigues, AG Green, O Kohlbacher, C Sander, … elife 3, e03430, 2014 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:iH-uZ7U-co4C

The developmental miRNA profiles of zebrafish as determined by small RNA cloning PY Chen, H Manninga, K Slanchev, M Chien, JJ Russo, J Ju, R Sheridan, … Genes & development 19 (11), 1288-1293, 2005 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:zYLM7Y9cAGgC

Disease variant prediction with deep generative models of evolutionary data J Frazer, P Notin, M Dias, A Gomez, JK Min, K Brock, Y Gal, DS Marks Nature 599 (7883), 91-95, 2021 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:2KloaMYe4IUC

MicroRNA control of protein expression noise JM Schmiedel, SL Klemm, Y Zheng, A Sahay, N Blüthgen, DS Marks, … Science 348 (6230), 128-132, 2015 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:GnPB-g6toBAC

Scientific discovery in the age of artificial intelligence H Wang, T Fu, Y Du, W Gao, K Huang, Z Liu, P Chandak, S Liu, … Nature 620 (7972), 47-60, 2023 Link: https://scholar.google.com/citations?viewop=viewcitation&hl=en&user=qFmoeNkAAAAJ&citationforview=qFmoeNkAAAAJ:S16KYo8Pm5AC

Co-authors

Chris Sander googlescholarauthorid chrissander.md:4R7_wW8AAAAJ

Thomas A. Hopf googlescholarauthorid thomasa._hopf.md:dK2eepUAAAAJ

John Ingraham googlescholarauthorid johningraham.md:qBarioAAAAAJ

Anton Enright googlescholarauthorid antonenright.md:kucwB9kAAAAJ

Anna G. Green googlescholarauthorid annag._green.md:o9rcausAAAAJ

Charlotta Scharfe googlescholarauthorid charlottascharfe.md:fCmpyIYAAAAJ

Riccardo Zecchina googlescholarauthorid riccardozecchina.md:fNOReswAAAAJ

Doron Betel googlescholarauthorid doronbetel.md:G5MjfRMAAAAJ

Christina Leslie googlescholarauthorid christinaleslie.md:e25-lgUAAAAJ

Andrea Pagnani googlescholarauthorid andreapagnani.md:EWJYRncAAAAJ

James J. Russo googlescholarauthorid jamesj._russo.md:UTY6T2MAAAAJ

Martin Weigt googlescholarauthorid martinweigt.md:HU1K_zsAAAAJ

Bryan J. Lunt googlescholarauthorid bryanj._lunt.md:XV30l4MAAAAJ

Erik Larsson Lekholm googlescholarauthorid eriklarsson_lekholm.md:m1lhgKgAAAAJ

Sébastien Pfeffer googlescholarauthorid sébastienpfeffer.md:zjm3WT0AAAAJ

Burkhard Rost googlescholarauthorid burkhardrost.md:BP3ofxcAAAAJ

Martin L Miller googlescholarauthorid martinl_miller.md:nuyBlicAAAAJ

Anders Jacobsen Skanderup googlescholarauthorid andersjacobsen_skanderup.md:r06O54MAAAAJ

Aaron Arvey googlescholarauthorid aaronarvey.md:W4isOSEAAAAJ

Kenneth S. Kosik googlescholarauthorid kenneths.kosik.md:4jg-CUAAAAJ

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Angstrom Levy Breaks Debbie's Arm When She Tells Him Hes The Bad Guy Invincible Season2 Episode 8

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