Biomedical ML

Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology

Eric Zimmermann, Eugene Vorontsov, Julian Viret, Adam Casson, Michal Zelechowski, George Shaikovski, Neil Tenenholtz, Jimmy Hall, Thomas J. Fuchs, Nicolo Fusi, Siqi Liu, Kristen Severson

July 2024

Publication

Discovering molecular features of intrinsically disordered regions by using evolution for contrastive learning

Alex X. Lu, Amy X. Lu, Iva Pritišanac, Taraneh Zarin, Julie D. Forman-Kay, Alan M. Moses

PLOS Computational Biology | July 2022, Vol 18(6)

Publication Projet

A Topological Data Analytic Approach for Discovering Biophysical Signatures in Protein Dynamics

W. S. Tang, G. M. da Silva, H. Kirveslahti, E. Skeens, B. Feng, T. Sudijono, Kevin Kaichuang Yang, S. Mukherjee, B. Rubenstein, Lorin Crawford

bioRxiv | July 2021

DOI

Discovery of Parkinson’s disease states and disease progression modelling: a longitudinal data study using machine learning

Kristen Severson, Lana M Chahine, Luba A Smolensky, Murtaza Dhuliawala, Mark Frasier, Kenney Ng, Soumya Ghosh, Jianying Hu

July 2021

DOI

Evidential Deep Learning for Guided Molecular Property Prediction and Discovery

Ava P. Amini, Alexander Amini, Samuel Goldman, Daniela Rus, Sangeeta N. Bhatia, Connor W. Coley

ACS central science | July 2021

DOI

MegaLMM: Mega-scale linear mixed models for genomic predictions with thousands of traits.

Daniel E. Runcie, Jiayi Qu, Hao Cheng, Lorin Crawford

Genome Biology | July 2021, Vol 22(1): pp. 213

DOI

A statistical pipeline for identifying physical features that differentiate classes of 3D shapes

Bruce Wang, Timothy Sudijono, Henry Kirveslahti, Tingran Gao, Douglas M. Boyer, Sayan Mukherjee, Lorin Crawford

The Annals of Applied Statistics | May 2021, Vol 15(2): pp. 638-661

DOI

Redefining replication in multi-ancestry genome-wide association studies

Smith Sp, Shahamatdar S, Cheng W, Zhang S, Paik J, Graff M, Haiman C, Matise T, North Ke, Peters U, Kenny E, Gignoux C, Wojcik G, Lorin Crawford, Ramachandran S

bioRxiv | April 2021

DOI

The tumor microenvironment drives transcriptional phenotypes and their plasticity in metastatic pancreatic cancer

Srivatsan Raghavan, Peter S. Winter, Andrew W. Navia, Hannah L. Williams, Alan DenAdel, Radha L. Kalekar, Jennyfer Galvez-Reyes, Kristen E. Lowder, Nolawit Mulugeta, Manisha S. Raghavan, Ashir A. Borah, Kevin S. Kapner, Sara A. Väyrynen, Andressa Dias Costa, Raymond W.S. Ng, Junning Wang, Emma Reilly, Dorisanne Y. Ragon, Lauren K. Brais, Alex M. Jaeger, Liam F. Spurr, Yvonne Y. Li, Andrew D. Cherniack, Isaac Wakiro, Asaf Rotem, Bruce E. Johnson, James M. McFarland, Ewa T. Sicinska, Tyler E. Jacks, Thomas E. Clancy, Kimberly Perez, Douglas A. Rubinson, Kimmie Ng, James M. Cleary, Lorin Crawford, Scott R. Manalis, Jonathan A. Nowak, Brian M. Wolpin, William C. Hahn, Andrew J. Aguirre, Alex K. Shalek

bioRxiv | April 2021

DOI

Natural variation in the regulation of neurodevelopmental genes modifies flight performance in Drosophila.

Adam N. Spierer, Jim A. Mossman, Samuel Pattillo Smith, Lorin Crawford, Sohini Ramachandran, David M. Rand

PLOS Genetics | March 2021, Vol 17(3)

DOI Publication

Activatable Zymography Probes Enable In Situ Localization of Protease Dysregulation in Cancer

Ava P. Soleimany, Jesse D. Kirkpatrick, Susan Su, Jaideep S. Dudani, Qian Zhong, Ahmet Bekdemir, Sangeeta N. Bhatia

Cancer Research | January 2021, Vol 81(1): pp. 213-224

DOI

Deep Evidential Regression

Alexander Amini, Wilko Schwarting, Ava Soleimany, Daniela Rus

2020 Neural Information Processing Systems | December 2020

PDF Publication

Generalizing Variational Autoencoders with Hierarchical Empirical Bayes.

Wei Cheng, Gregory Darnell, Sohini Ramachandran, Lorin Crawford

arXiv | July 2020

Publication

Multi-scale Genomic Inference using Biologically Annotated Neural Networks

Pinar Demetci, Wei Cheng, Gregory Darnell, Xiang Zhou, Sohini Ramachandran, Lorin Crawford

bioRxiv | July 2020

DOI PDF Publication

Predicting Clinical Outcomes in Glioblastoma: An Application of Topological and Functional Data Analysis

Lorin Crawford, Anthea Monod, Andrew X. Chen, Sayan Mukherjee, Raúl Rabadán

Journal of the American Statistical Association | July 2020, Vol 115(531): pp. 1139-1150

DOI

Estimation of non-null SNP effect size distributions enables the detection of enriched genes underlying complex traits.

Wei Cheng, Sohini Ramachandran, Lorin Crawford

PLOS Genetics | June 2020, Vol 16(6): pp. 1139-1150

DOI

Pharmacokinetic tuning of protein-antigen fusions enhances the immunogenicity of T-cell vaccines

Naveen K Mehta, Roma V Pradhan, Ava P. Soleimany, Kelly D Moynihan, Adrienne M Rothschilds, Noor Momin, Kavya Rakhra, Jordi Mata-Fink, Sangeeta N Bhatia, K Dane Wittrup, Darrell J Irvine

Nature Biomedical Engineering | May 2020, Vol 4(6): pp. 636-648

DOI Projet

Activity-Based Diagnostics: An Emerging Paradigm for Disease Detection and Monitoring

Ava P. Soleimany, Sangeeta N. Bhatia

Trends in Molecular Medicine | April 2020, Vol 26(5): pp. 450-468

DOI

Convergent evolution of p38/MAPK activation in hormone resistant prostate cancer mediates pro-survival, immune evasive, and metastatic phenotypes

Kathryn E. Ware, Santosh Gupta, Jared Eng, Gabor Kemeny, Bhairavy J. Puviindran, Wen-Chi Foo, Lorin Crawford, R. Garland Almquist, Daniella Runyambo, Beatrice C. Thomas, Maya U. Sheth, Anika Agarwal, Mariaelena Pierobon, Emanuel F. Petricoin, David L. Corcoran, Jennifer Freedman, Steven R. Patierno, Tian Zhang, Simon Gregory, Zoi Sychev, Justin M. Drake, Andrew J. Armstrong, Jason A. Somarelli

bioRxiv | April 2020

DOI

DPVis: Visual Analytics With Hidden Markov Models for Disease Progression Pathways.

Bum Chul Kwon, Vibha Anand, Kristen Severson, Soumya Ghosh, Zhaonan Sun, Brigitte I Frohnert, Markus Lundgren, Kenney Ng

IEEE Transactions on Visualization and Computer Graphics | April 2020, Vol 27(9): pp. 3685-3700

DOI

Urinary detection of lung cancer in mice via noninvasive pulmonary protease profiling

Jesse D. Kirkpatrick, Andrew D. Warren, Ava P. Soleimany, Peter M. K. Westcott, Justin C. Voog, Carmen Martin-Alonso, Heather E. Fleming, Tuomas Tammela, Tyler Jacks, Sangeeta N. Bhatia

Science Translational Medicine | March 2020, Vol 12(537)

DOI

Personalized Input-Output Hidden Markov Models for Disease Progression Modeling.

Kristen Severson, Lana M. Chahine, Luba Smolensky, Kenney Ng, Jianying Hu, Soumya Ghosh

December 2019

Publication

Machine learning-guided channelrhodopsin engineering enables minimally invasive optogenetics.

Claire N. Bedbrook, Kevin Kaichuang Yang, J. Elliott Robinson, Elisha D. Mackey, Viviana Gradinaru, Frances H. Arnold

Nature Methods | October 2019, Vol 16(11): pp. 1176-1184

DOI

Renal clearable catalytic gold nanoclusters for in vivo disease monitoring

Colleen N. Loynachan, Ava P. Soleimany, Jaideep S. Dudani, Yiyang Lin, Adrian Najer, Ahmet Bekdemir, Qu Chen, Sangeeta N. Bhatia, Molly M. Stevens

Nature Nanotechnology | August 2019, Vol 14(9): pp. 883-890

DOI

Stem cells and extracellular vesicles: biological regulators of physiology and disease.

Theodor Borgovan, Lorin Crawford, Chibuikem Nwizu, Peter Quesenberry

American Journal of Physiology-cell Physiology | July 2019, Vol 317(2)

DOI

Unsupervised Learning with Contrastive Latent Variable Models

Kristen Severson, Soumya Ghosh, Kenney Ng

2019 National Conference on Artificial Intelligence | July 2019

DOI

Machine-learning-guided directed evolution for protein engineering.

Kevin Kaichuang Yang, Zachary Wu, Frances H Arnold

Nature Methods | July 2019, Vol 16(8): pp. 687-694

DOI

Fast and flexible linear mixed models for genome-wide genetics.

Daniel E. Runcie, Lorin Crawford

PLOS Genetics | February 2019, Vol 15(2): pp. 1-24

DOI

Interpreting Deep Neural Networks Through Variable Importance.

Jonathan Ish-Horowicz, Dana Udwin, Seth R. Flaxman, Sarah Filippi, Lorin Crawford

arXiv | January 2019

Publication

Uncovering and Mitigating Algorithmic Bias through Learned Latent Structure

Alexander Amini, Ava P. Soleimany, Wilko Schwarting, Sangeeta N. Bhatia, Daniela Rus

AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society | January 2019

DOI

Genome-wide Marginal Epistatic Association Mapping in Case-Control Studies

Lorin Crawford, Xiang Zhou

bioRxiv | July 2018

DOI

Bayesian Approximate Kernel Regression with Variable Selection

Lorin Crawford, Kris C. Wood, Xiang Zhou, Sayan Mukherjee

Journal of the American Statistical Association | June 2018, Vol 113(524): pp. 1710-1721

DOI

Orthologous CRISPR–Cas9 enzymes for combinatorial genetic screens

Nicolo Fusi, et al

nature biotechnology | October 2017, Vol 36: pp. 179-189

Publication

On the challenges of learning with inference networks on sparse, high-dimensional data

Rahul Gopalkrishnan, Dawen Liang, Matthew D. Hoffman

International Conference on Artificial Intelligence and Statistics | October 2017

PDF Publication

Detecting epistasis with the marginal epistasis test in genetic mapping studies of quantitative traits.

Lorin Crawford, Ping Zeng, Sayan Mukherjee, Xiang Zhou

PLOS Genetics | July 2017, Vol 13(7)

DOI

Synthetic recombinase-based state machines in living cells

Nathaniel Roquet, Ava P. Soleimany, Alyssa C. Ferris, Scott Aaronson, Timothy K. Lu

Science | July 2016, Vol 353(6297): pp. 363-363

DOI

Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9

John G. Doench, Nicolo Fusi, Meagan Sullender, Mudra Hegde, Emma W. Vaimberg, Katherine F. Donovan, Ian Smith, Zuzana Tothova, Craig Wilen, Robert Orchard, Herbert W. Virgin, Jennifer Listgarten, David E. Root

nature biotechnology | January 2016, pp. 184-191

Publication

Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology

Eric Zimmermann, Eugene Vorontsov, Julian Viret, Adam Casson, Michal Zelechowski, George Shaikovski, Neil Tenenholtz, Jimmy Hall, Thomas J. Fuchs, Nicolo Fusi, Siqi Liu, Kristen Severson

July 2024

Publication

Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology

Eric Zimmermann, Eugene Vorontsov, Julian Viret, Adam Casson, Michal Zelechowski, George Shaikovski, Neil Tenenholtz, Jimmy Hall, Thomas J. Fuchs, Nicolo Fusi, Siqi Liu, Kristen Severson

July 2024

Publication

Discovering molecular features of intrinsically disordered regions by using evolution for contrastive learning

Alex X. Lu, Amy X. Lu, Iva Pritišanac, Taraneh Zarin, Julie D. Forman-Kay, Alan M. Moses

PLOS Computational Biology | July 2022, Vol 18(6)

Publication Projet

A Topological Data Analytic Approach for Discovering Biophysical Signatures in Protein Dynamics

W. S. Tang, G. M. da Silva, H. Kirveslahti, E. Skeens, B. Feng, T. Sudijono, Kevin Kaichuang Yang, S. Mukherjee, B. Rubenstein, Lorin Crawford

bioRxiv | July 2021

DOI

Discovery of Parkinson’s disease states and disease progression modelling: a longitudinal data study using machine learning

Kristen Severson, Lana M Chahine, Luba A Smolensky, Murtaza Dhuliawala, Mark Frasier, Kenney Ng, Soumya Ghosh, Jianying Hu

July 2021

DOI

Evidential Deep Learning for Guided Molecular Property Prediction and Discovery

Ava P. Amini, Alexander Amini, Samuel Goldman, Daniela Rus, Sangeeta N. Bhatia, Connor W. Coley

ACS central science | July 2021

DOI

MegaLMM: Mega-scale linear mixed models for genomic predictions with thousands of traits.

Daniel E. Runcie, Jiayi Qu, Hao Cheng, Lorin Crawford

Genome Biology | July 2021, Vol 22(1): pp. 213

DOI

A statistical pipeline for identifying physical features that differentiate classes of 3D shapes

Bruce Wang, Timothy Sudijono, Henry Kirveslahti, Tingran Gao, Douglas M. Boyer, Sayan Mukherjee, Lorin Crawford

The Annals of Applied Statistics | May 2021, Vol 15(2): pp. 638-661

DOI

Redefining replication in multi-ancestry genome-wide association studies

Smith Sp, Shahamatdar S, Cheng W, Zhang S, Paik J, Graff M, Haiman C, Matise T, North Ke, Peters U, Kenny E, Gignoux C, Wojcik G, Lorin Crawford, Ramachandran S

bioRxiv | April 2021

DOI

The tumor microenvironment drives transcriptional phenotypes and their plasticity in metastatic pancreatic cancer

Srivatsan Raghavan, Peter S. Winter, Andrew W. Navia, Hannah L. Williams, Alan DenAdel, Radha L. Kalekar, Jennyfer Galvez-Reyes, Kristen E. Lowder, Nolawit Mulugeta, Manisha S. Raghavan, Ashir A. Borah, Kevin S. Kapner, Sara A. Väyrynen, Andressa Dias Costa, Raymond W.S. Ng, Junning Wang, Emma Reilly, Dorisanne Y. Ragon, Lauren K. Brais, Alex M. Jaeger, Liam F. Spurr, Yvonne Y. Li, Andrew D. Cherniack, Isaac Wakiro, Asaf Rotem, Bruce E. Johnson, James M. McFarland, Ewa T. Sicinska, Tyler E. Jacks, Thomas E. Clancy, Kimberly Perez, Douglas A. Rubinson, Kimmie Ng, James M. Cleary, Lorin Crawford, Scott R. Manalis, Jonathan A. Nowak, Brian M. Wolpin, William C. Hahn, Andrew J. Aguirre, Alex K. Shalek

bioRxiv | April 2021

DOI

Natural variation in the regulation of neurodevelopmental genes modifies flight performance in Drosophila.

Adam N. Spierer, Jim A. Mossman, Samuel Pattillo Smith, Lorin Crawford, Sohini Ramachandran, David M. Rand

PLOS Genetics | March 2021, Vol 17(3)

DOI Publication

Activatable Zymography Probes Enable In Situ Localization of Protease Dysregulation in Cancer

Ava P. Soleimany, Jesse D. Kirkpatrick, Susan Su, Jaideep S. Dudani, Qian Zhong, Ahmet Bekdemir, Sangeeta N. Bhatia

Cancer Research | January 2021, Vol 81(1): pp. 213-224

DOI

Generalizing Variational Autoencoders with Hierarchical Empirical Bayes.

Wei Cheng, Gregory Darnell, Sohini Ramachandran, Lorin Crawford

arXiv | July 2020

Publication

Multi-scale Genomic Inference using Biologically Annotated Neural Networks

Pinar Demetci, Wei Cheng, Gregory Darnell, Xiang Zhou, Sohini Ramachandran, Lorin Crawford

bioRxiv | July 2020

DOI PDF Publication

Predicting Clinical Outcomes in Glioblastoma: An Application of Topological and Functional Data Analysis

Lorin Crawford, Anthea Monod, Andrew X. Chen, Sayan Mukherjee, Raúl Rabadán

Journal of the American Statistical Association | July 2020, Vol 115(531): pp. 1139-1150

DOI

Estimation of non-null SNP effect size distributions enables the detection of enriched genes underlying complex traits.

Wei Cheng, Sohini Ramachandran, Lorin Crawford

PLOS Genetics | June 2020, Vol 16(6): pp. 1139-1150

DOI

Pharmacokinetic tuning of protein-antigen fusions enhances the immunogenicity of T-cell vaccines

Naveen K Mehta, Roma V Pradhan, Ava P. Soleimany, Kelly D Moynihan, Adrienne M Rothschilds, Noor Momin, Kavya Rakhra, Jordi Mata-Fink, Sangeeta N Bhatia, K Dane Wittrup, Darrell J Irvine

Nature Biomedical Engineering | May 2020, Vol 4(6): pp. 636-648

DOI Projet

Activity-Based Diagnostics: An Emerging Paradigm for Disease Detection and Monitoring

Ava P. Soleimany, Sangeeta N. Bhatia

Trends in Molecular Medicine | April 2020, Vol 26(5): pp. 450-468

DOI

Convergent evolution of p38/MAPK activation in hormone resistant prostate cancer mediates pro-survival, immune evasive, and metastatic phenotypes

Kathryn E. Ware, Santosh Gupta, Jared Eng, Gabor Kemeny, Bhairavy J. Puviindran, Wen-Chi Foo, Lorin Crawford, R. Garland Almquist, Daniella Runyambo, Beatrice C. Thomas, Maya U. Sheth, Anika Agarwal, Mariaelena Pierobon, Emanuel F. Petricoin, David L. Corcoran, Jennifer Freedman, Steven R. Patierno, Tian Zhang, Simon Gregory, Zoi Sychev, Justin M. Drake, Andrew J. Armstrong, Jason A. Somarelli

bioRxiv | April 2020

DOI

DPVis: Visual Analytics With Hidden Markov Models for Disease Progression Pathways.

Bum Chul Kwon, Vibha Anand, Kristen Severson, Soumya Ghosh, Zhaonan Sun, Brigitte I Frohnert, Markus Lundgren, Kenney Ng

IEEE Transactions on Visualization and Computer Graphics | April 2020, Vol 27(9): pp. 3685-3700

DOI

Urinary detection of lung cancer in mice via noninvasive pulmonary protease profiling

Jesse D. Kirkpatrick, Andrew D. Warren, Ava P. Soleimany, Peter M. K. Westcott, Justin C. Voog, Carmen Martin-Alonso, Heather E. Fleming, Tuomas Tammela, Tyler Jacks, Sangeeta N. Bhatia

Science Translational Medicine | March 2020, Vol 12(537)

DOI

Personalized Input-Output Hidden Markov Models for Disease Progression Modeling.

Kristen Severson, Lana M. Chahine, Luba Smolensky, Kenney Ng, Jianying Hu, Soumya Ghosh

December 2019

Publication

Machine learning-guided channelrhodopsin engineering enables minimally invasive optogenetics.

Claire N. Bedbrook, Kevin Kaichuang Yang, J. Elliott Robinson, Elisha D. Mackey, Viviana Gradinaru, Frances H. Arnold

Nature Methods | October 2019, Vol 16(11): pp. 1176-1184

DOI

Renal clearable catalytic gold nanoclusters for in vivo disease monitoring

Colleen N. Loynachan, Ava P. Soleimany, Jaideep S. Dudani, Yiyang Lin, Adrian Najer, Ahmet Bekdemir, Qu Chen, Sangeeta N. Bhatia, Molly M. Stevens

Nature Nanotechnology | August 2019, Vol 14(9): pp. 883-890

DOI

Stem cells and extracellular vesicles: biological regulators of physiology and disease.

Theodor Borgovan, Lorin Crawford, Chibuikem Nwizu, Peter Quesenberry

American Journal of Physiology-cell Physiology | July 2019, Vol 317(2)

DOI

Unsupervised Learning with Contrastive Latent Variable Models

Kristen Severson, Soumya Ghosh, Kenney Ng

2019 National Conference on Artificial Intelligence | July 2019

DOI

Machine-learning-guided directed evolution for protein engineering.

Kevin Kaichuang Yang, Zachary Wu, Frances H Arnold

Nature Methods | July 2019, Vol 16(8): pp. 687-694

DOI

Fast and flexible linear mixed models for genome-wide genetics.

Daniel E. Runcie, Lorin Crawford

PLOS Genetics | February 2019, Vol 15(2): pp. 1-24

DOI

Interpreting Deep Neural Networks Through Variable Importance.

Jonathan Ish-Horowicz, Dana Udwin, Seth R. Flaxman, Sarah Filippi, Lorin Crawford

arXiv | January 2019

Publication

Uncovering and Mitigating Algorithmic Bias through Learned Latent Structure

Alexander Amini, Ava P. Soleimany, Wilko Schwarting, Sangeeta N. Bhatia, Daniela Rus

AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society | January 2019

DOI

Genome-wide Marginal Epistatic Association Mapping in Case-Control Studies

Lorin Crawford, Xiang Zhou

bioRxiv | July 2018

DOI

Bayesian Approximate Kernel Regression with Variable Selection

Lorin Crawford, Kris C. Wood, Xiang Zhou, Sayan Mukherjee

Journal of the American Statistical Association | June 2018, Vol 113(524): pp. 1710-1721

DOI

Orthologous CRISPR–Cas9 enzymes for combinatorial genetic screens

Nicolo Fusi, et al

nature biotechnology | October 2017, Vol 36: pp. 179-189

Publication

On the challenges of learning with inference networks on sparse, high-dimensional data

Rahul Gopalkrishnan, Dawen Liang, Matthew D. Hoffman

International Conference on Artificial Intelligence and Statistics | October 2017

PDF Publication

Detecting epistasis with the marginal epistasis test in genetic mapping studies of quantitative traits.

Lorin Crawford, Ping Zeng, Sayan Mukherjee, Xiang Zhou

PLOS Genetics | July 2017, Vol 13(7)

DOI

Synthetic recombinase-based state machines in living cells

Nathaniel Roquet, Ava P. Soleimany, Alyssa C. Ferris, Scott Aaronson, Timothy K. Lu

Science | July 2016, Vol 353(6297): pp. 363-363

DOI

Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9

John G. Doench, Nicolo Fusi, Meagan Sullender, Mudra Hegde, Emma W. Vaimberg, Katherine F. Donovan, Ian Smith, Zuzana Tothova, Craig Wilen, Robert Orchard, Herbert W. Virgin, Jennifer Listgarten, David E. Root

nature biotechnology | January 2016, pp. 184-191

Publication

Discovering molecular features of intrinsically disordered regions by using evolution for contrastive learning

Alex X. Lu, Amy X. Lu, Iva Pritišanac, Taraneh Zarin, Julie D. Forman-Kay, Alan M. Moses

PLOS Computational Biology | July 2022, Vol 18(6)

Publication Projet

Deep Evidential Regression

Alexander Amini, Wilko Schwarting, Ava Soleimany, Daniela Rus

2020 Neural Information Processing Systems | December 2020

PDF Publication

Urinary detection of lung cancer in mice via noninvasive pulmonary protease profiling

Jesse D. Kirkpatrick, Andrew D. Warren, Ava P. Soleimany, Peter M. K. Westcott, Justin C. Voog, Carmen Martin-Alonso, Heather E. Fleming, Tuomas Tammela, Tyler Jacks, Sangeeta N. Bhatia

Science Translational Medicine | March 2020, Vol 12(537)

DOI

Synthetic recombinase-based state machines in living cells

Nathaniel Roquet, Ava P. Soleimany, Alyssa C. Ferris, Scott Aaronson, Timothy K. Lu

Science | July 2016, Vol 353(6297): pp. 363-363

DOI

Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology

Eric Zimmermann, Eugene Vorontsov, Julian Viret, Adam Casson, Michal Zelechowski, George Shaikovski, Neil Tenenholtz, Jimmy Hall, Thomas J. Fuchs, Nicolo Fusi, Siqi Liu, Kristen Severson

July 2024

Publication

Discovery of Parkinson’s disease states and disease progression modelling: a longitudinal data study using machine learning

Kristen Severson, Lana M Chahine, Luba A Smolensky, Murtaza Dhuliawala, Mark Frasier, Kenney Ng, Soumya Ghosh, Jianying Hu

July 2021

DOI

Personalized Input-Output Hidden Markov Models for Disease Progression Modeling.

Kristen Severson, Lana M. Chahine, Luba Smolensky, Kenney Ng, Jianying Hu, Soumya Ghosh

December 2019

Publication

Discovering molecular features of intrinsically disordered regions by using evolution for contrastive learning

Alex X. Lu, Amy X. Lu, Iva Pritišanac, Taraneh Zarin, Julie D. Forman-Kay, Alan M. Moses

PLOS Computational Biology | July 2022, Vol 18(6)

Publication Projet

A Topological Data Analytic Approach for Discovering Biophysical Signatures in Protein Dynamics

W. S. Tang, G. M. da Silva, H. Kirveslahti, E. Skeens, B. Feng, T. Sudijono, Kevin Kaichuang Yang, S. Mukherjee, B. Rubenstein, Lorin Crawford

bioRxiv | July 2021

DOI

Evidential Deep Learning for Guided Molecular Property Prediction and Discovery

Ava P. Amini, Alexander Amini, Samuel Goldman, Daniela Rus, Sangeeta N. Bhatia, Connor W. Coley

ACS central science | July 2021

DOI

MegaLMM: Mega-scale linear mixed models for genomic predictions with thousands of traits.

Daniel E. Runcie, Jiayi Qu, Hao Cheng, Lorin Crawford

Genome Biology | July 2021, Vol 22(1): pp. 213

DOI

A statistical pipeline for identifying physical features that differentiate classes of 3D shapes

Bruce Wang, Timothy Sudijono, Henry Kirveslahti, Tingran Gao, Douglas M. Boyer, Sayan Mukherjee, Lorin Crawford

The Annals of Applied Statistics | May 2021, Vol 15(2): pp. 638-661

DOI

Redefining replication in multi-ancestry genome-wide association studies

Smith Sp, Shahamatdar S, Cheng W, Zhang S, Paik J, Graff M, Haiman C, Matise T, North Ke, Peters U, Kenny E, Gignoux C, Wojcik G, Lorin Crawford, Ramachandran S

bioRxiv | April 2021

DOI

The tumor microenvironment drives transcriptional phenotypes and their plasticity in metastatic pancreatic cancer

Srivatsan Raghavan, Peter S. Winter, Andrew W. Navia, Hannah L. Williams, Alan DenAdel, Radha L. Kalekar, Jennyfer Galvez-Reyes, Kristen E. Lowder, Nolawit Mulugeta, Manisha S. Raghavan, Ashir A. Borah, Kevin S. Kapner, Sara A. Väyrynen, Andressa Dias Costa, Raymond W.S. Ng, Junning Wang, Emma Reilly, Dorisanne Y. Ragon, Lauren K. Brais, Alex M. Jaeger, Liam F. Spurr, Yvonne Y. Li, Andrew D. Cherniack, Isaac Wakiro, Asaf Rotem, Bruce E. Johnson, James M. McFarland, Ewa T. Sicinska, Tyler E. Jacks, Thomas E. Clancy, Kimberly Perez, Douglas A. Rubinson, Kimmie Ng, James M. Cleary, Lorin Crawford, Scott R. Manalis, Jonathan A. Nowak, Brian M. Wolpin, William C. Hahn, Andrew J. Aguirre, Alex K. Shalek

bioRxiv | April 2021

DOI

Natural variation in the regulation of neurodevelopmental genes modifies flight performance in Drosophila.

Adam N. Spierer, Jim A. Mossman, Samuel Pattillo Smith, Lorin Crawford, Sohini Ramachandran, David M. Rand

PLOS Genetics | March 2021, Vol 17(3)

DOI Publication

Activatable Zymography Probes Enable In Situ Localization of Protease Dysregulation in Cancer

Ava P. Soleimany, Jesse D. Kirkpatrick, Susan Su, Jaideep S. Dudani, Qian Zhong, Ahmet Bekdemir, Sangeeta N. Bhatia

Cancer Research | January 2021, Vol 81(1): pp. 213-224

DOI

Generalizing Variational Autoencoders with Hierarchical Empirical Bayes.

Wei Cheng, Gregory Darnell, Sohini Ramachandran, Lorin Crawford

arXiv | July 2020

Publication

Multi-scale Genomic Inference using Biologically Annotated Neural Networks

Pinar Demetci, Wei Cheng, Gregory Darnell, Xiang Zhou, Sohini Ramachandran, Lorin Crawford

bioRxiv | July 2020

DOI PDF Publication

Predicting Clinical Outcomes in Glioblastoma: An Application of Topological and Functional Data Analysis

Lorin Crawford, Anthea Monod, Andrew X. Chen, Sayan Mukherjee, Raúl Rabadán

Journal of the American Statistical Association | July 2020, Vol 115(531): pp. 1139-1150

DOI

Estimation of non-null SNP effect size distributions enables the detection of enriched genes underlying complex traits.

Wei Cheng, Sohini Ramachandran, Lorin Crawford

PLOS Genetics | June 2020, Vol 16(6): pp. 1139-1150

DOI

Pharmacokinetic tuning of protein-antigen fusions enhances the immunogenicity of T-cell vaccines

Naveen K Mehta, Roma V Pradhan, Ava P. Soleimany, Kelly D Moynihan, Adrienne M Rothschilds, Noor Momin, Kavya Rakhra, Jordi Mata-Fink, Sangeeta N Bhatia, K Dane Wittrup, Darrell J Irvine

Nature Biomedical Engineering | May 2020, Vol 4(6): pp. 636-648

DOI Projet

Activity-Based Diagnostics: An Emerging Paradigm for Disease Detection and Monitoring

Ava P. Soleimany, Sangeeta N. Bhatia

Trends in Molecular Medicine | April 2020, Vol 26(5): pp. 450-468

DOI

Convergent evolution of p38/MAPK activation in hormone resistant prostate cancer mediates pro-survival, immune evasive, and metastatic phenotypes

Kathryn E. Ware, Santosh Gupta, Jared Eng, Gabor Kemeny, Bhairavy J. Puviindran, Wen-Chi Foo, Lorin Crawford, R. Garland Almquist, Daniella Runyambo, Beatrice C. Thomas, Maya U. Sheth, Anika Agarwal, Mariaelena Pierobon, Emanuel F. Petricoin, David L. Corcoran, Jennifer Freedman, Steven R. Patierno, Tian Zhang, Simon Gregory, Zoi Sychev, Justin M. Drake, Andrew J. Armstrong, Jason A. Somarelli

bioRxiv | April 2020

DOI

DPVis: Visual Analytics With Hidden Markov Models for Disease Progression Pathways.

Bum Chul Kwon, Vibha Anand, Kristen Severson, Soumya Ghosh, Zhaonan Sun, Brigitte I Frohnert, Markus Lundgren, Kenney Ng

IEEE Transactions on Visualization and Computer Graphics | April 2020, Vol 27(9): pp. 3685-3700

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Urinary detection of lung cancer in mice via noninvasive pulmonary protease profiling

Jesse D. Kirkpatrick, Andrew D. Warren, Ava P. Soleimany, Peter M. K. Westcott, Justin C. Voog, Carmen Martin-Alonso, Heather E. Fleming, Tuomas Tammela, Tyler Jacks, Sangeeta N. Bhatia

Science Translational Medicine | March 2020, Vol 12(537)

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Machine learning-guided channelrhodopsin engineering enables minimally invasive optogenetics.

Claire N. Bedbrook, Kevin Kaichuang Yang, J. Elliott Robinson, Elisha D. Mackey, Viviana Gradinaru, Frances H. Arnold

Nature Methods | October 2019, Vol 16(11): pp. 1176-1184

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Renal clearable catalytic gold nanoclusters for in vivo disease monitoring

Colleen N. Loynachan, Ava P. Soleimany, Jaideep S. Dudani, Yiyang Lin, Adrian Najer, Ahmet Bekdemir, Qu Chen, Sangeeta N. Bhatia, Molly M. Stevens

Nature Nanotechnology | August 2019, Vol 14(9): pp. 883-890

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Stem cells and extracellular vesicles: biological regulators of physiology and disease.

Theodor Borgovan, Lorin Crawford, Chibuikem Nwizu, Peter Quesenberry

American Journal of Physiology-cell Physiology | July 2019, Vol 317(2)

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Machine-learning-guided directed evolution for protein engineering.

Kevin Kaichuang Yang, Zachary Wu, Frances H Arnold

Nature Methods | July 2019, Vol 16(8): pp. 687-694

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Fast and flexible linear mixed models for genome-wide genetics.

Daniel E. Runcie, Lorin Crawford

PLOS Genetics | February 2019, Vol 15(2): pp. 1-24

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Interpreting Deep Neural Networks Through Variable Importance.

Jonathan Ish-Horowicz, Dana Udwin, Seth R. Flaxman, Sarah Filippi, Lorin Crawford

arXiv | January 2019

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Genome-wide Marginal Epistatic Association Mapping in Case-Control Studies

Lorin Crawford, Xiang Zhou

bioRxiv | July 2018

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Bayesian Approximate Kernel Regression with Variable Selection

Lorin Crawford, Kris C. Wood, Xiang Zhou, Sayan Mukherjee

Journal of the American Statistical Association | June 2018, Vol 113(524): pp. 1710-1721

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Orthologous CRISPR–Cas9 enzymes for combinatorial genetic screens

Nicolo Fusi, et al

nature biotechnology | October 2017, Vol 36: pp. 179-189

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Detecting epistasis with the marginal epistasis test in genetic mapping studies of quantitative traits.

Lorin Crawford, Ping Zeng, Sayan Mukherjee, Xiang Zhou

PLOS Genetics | July 2017, Vol 13(7)

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Synthetic recombinase-based state machines in living cells

Nathaniel Roquet, Ava P. Soleimany, Alyssa C. Ferris, Scott Aaronson, Timothy K. Lu

Science | July 2016, Vol 353(6297): pp. 363-363

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Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9

John G. Doench, Nicolo Fusi, Meagan Sullender, Mudra Hegde, Emma W. Vaimberg, Katherine F. Donovan, Ian Smith, Zuzana Tothova, Craig Wilen, Robert Orchard, Herbert W. Virgin, Jennifer Listgarten, David E. Root

nature biotechnology | January 2016, pp. 184-191

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Deep Evidential Regression

Alexander Amini, Wilko Schwarting, Ava Soleimany, Daniela Rus

2020 Neural Information Processing Systems | December 2020

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Unsupervised Learning with Contrastive Latent Variable Models

Kristen Severson, Soumya Ghosh, Kenney Ng

2019 National Conference on Artificial Intelligence | July 2019

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Uncovering and Mitigating Algorithmic Bias through Learned Latent Structure

Alexander Amini, Ava P. Soleimany, Wilko Schwarting, Sangeeta N. Bhatia, Daniela Rus

AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society | January 2019

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On the challenges of learning with inference networks on sparse, high-dimensional data

Rahul Gopalkrishnan, Dawen Liang, Matthew D. Hoffman

International Conference on Artificial Intelligence and Statistics | October 2017

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