Project Ex Vivo

Defining, engineering, and targeting cell states in cancer

Microsoft & the Broad Institute

论文与出版物

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- Consequences of training data composition for deep learning models in single-cell biology
  
  Ajay Nadig, Akshaya Thoutam, Madeline Hughes, Anay Gupta, Andrew W. Navia, Nicolo Fusi, Srivatsan Raghavan, Peter S. Winter, Ava P. Amini, Lorin Crawford
  
  bioRxiv | February 2025
  
  Publication DOI
- Evaluating the role of pre-training dataset size and diversity on single-cell foundation model performance
  
  Alan DenAdel, Madeline Hughes, Akshaya Thoutam, Anay Gupta, Nicolo Fusi, Andrew W. Navia, Srivatsan Raghavan, Peter S. Winter, Ava P. Amini, Lorin Crawford
  
  bioRxiv | December 2024
  
  Preprint
- Scalable, compressed phenotypic screening using pooled perturbations.
  
  Nuo Liu, Walaa E. Kattan, Benjamin E. Mead, Conner Kummerlowe, Thomas Cheng, Sarah Ingabire, Jaime H Cheah, Christian K Soule, Anita Vrcic, Jane K. McIninch, Sergio Triana, Manuel Guzman, Tyler T. Dao, Joshua M. Peters, Kristen E. Lowder, Lorin Crawford, Ava P. Amini, Paul C. Blainey, William C. Hahn, Brian Cleary, Bryan D. Bryson, Peter S. Winter, Srivatsan Raghavan, Alex K. Shalek
  
  Nature biotechnology | October 2024
  
  DOI Publication
- Mutation and cell state compatibility is required and targetable in Ph+ acute lymphoblastic leukemia minimal residual disease
  
  Peter S. Winter, Michelle L. Ramseier, Andrew W. Navia, Sachit D. Saksena, Haley Strouf, Nezha Senhaji, Alan DenAdel, Mahnoor Mirza, Hyun Hwan An, Laura L. Bilal, Peter Dennis, Catharine S. Leahy, Kay Shigemori, Jennyfer Galves-Reyes, Ye Zhang, Foster Powers, Nolawit Mulugeta, Alejandro J. Gupta, Nicholas L. Calistri, Alexandria van Scoyk, Kristen Jones, Huiyun Liu, Kristen Stevenson, S. Ren, M. Luskin, Charles P. Couturier, Ava P. Amini, Srivatsan Raghavan, Robert J. Kimmerling, Mark M. Stevens, Lorin Crawford, David M. Weinstock, Scott R. Manalis, Alex K. Shalek, Mark A. Murakami
  
  bioRxiv | June 2024
  
  Preprint
- A knockoff calibration method to avoid over-clustering in single-cell RNA-sequencing
  
  Alan DenAdel, Michelle L. Ramseier, Andrew W. Navia, Alex K. Shalek, Srivatsan Raghavan, Peter S. Winter, Ava P. Amini, Lorin Crawford
  
  bioRxiv | March 2024
  
  Preprint
- Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data
  
  Chibuikem Nwizu, Madeline Hughes, Michelle L. Ramseier, Andrew W. Navia, Alex K. Shalek, Nicolo Fusi, Srivatsan Raghavan, Peter S. Winter, Ava P. Amini, Lorin Crawford
  
  bioRxiv | February 2024
  
  Preprint
- Assessing the limits of zero-shot foundation models in single-cell biology
  
  Kasia Z. Kedzierska, Lorin Crawford, Ava P. Amini, Alex Lu
  
  bioRxiv | November 2023
  
  Preprint PDF
- Microenvironment drives cell state, plasticity, and drug response in pancreatic cancer
  
  Srivatsan Raghavan, Peter S. Winter, Andrew W Navia, Hannah L. Williams, Alan DenAdel, Kristen E. Lowder, Jennyfer Galvez-Reyes, R. Kalekar, Nolawit Mulugeta, Kevin S. Kapner, M. Raghavan, Ashir A. Borah, Nuo Liu, Sara A. Väyrynen, Andressa Dias Costa, R. Ng, Junning Wang, Emma K. Hill, Dorisanne Y. Ragon, L. Brais, Alex M. Jaeger, Liam F. Spurr, Yvonne Y. Li, A. Cherniack, M. Booker, Elizabeth F Cohen, M. Tolstorukov, Isaac Wakiro, Asaf Rotem, B. Johnson, James M. McFarland, E. Sicinska, T. Jacks, R. Sullivan, G. Shapiro, T. Clancy, Kimberly Perez, D. Rubinson, K. Ng, J. Cleary, Lorin Crawford, S. Manalis, J. Nowak, B. Wolpin, William C. Hahn, A. Aguirre, A. Shalek
  
  PubMed Cell | November 2021, 第 184 卷: pp. 6119-6137.e26
  
  DOI Publication Publication

- Consequences of training data composition for deep learning models in single-cell biology
  
  Ajay Nadig, Akshaya Thoutam, Madeline Hughes, Anay Gupta, Andrew W. Navia, Nicolo Fusi, Srivatsan Raghavan, Peter S. Winter, Ava P. Amini, Lorin Crawford
  
  bioRxiv | February 2025
  
  Publication DOI
- Evaluating the role of pre-training dataset size and diversity on single-cell foundation model performance
  
  Alan DenAdel, Madeline Hughes, Akshaya Thoutam, Anay Gupta, Nicolo Fusi, Andrew W. Navia, Srivatsan Raghavan, Peter S. Winter, Ava P. Amini, Lorin Crawford
  
  bioRxiv | December 2024
  
  Preprint
- Scalable, compressed phenotypic screening using pooled perturbations.
  
  Nuo Liu, Walaa E. Kattan, Benjamin E. Mead, Conner Kummerlowe, Thomas Cheng, Sarah Ingabire, Jaime H Cheah, Christian K Soule, Anita Vrcic, Jane K. McIninch, Sergio Triana, Manuel Guzman, Tyler T. Dao, Joshua M. Peters, Kristen E. Lowder, Lorin Crawford, Ava P. Amini, Paul C. Blainey, William C. Hahn, Brian Cleary, Bryan D. Bryson, Peter S. Winter, Srivatsan Raghavan, Alex K. Shalek
  
  Nature biotechnology | October 2024
  
  DOI Publication
- Mutation and cell state compatibility is required and targetable in Ph+ acute lymphoblastic leukemia minimal residual disease
  
  Peter S. Winter, Michelle L. Ramseier, Andrew W. Navia, Sachit D. Saksena, Haley Strouf, Nezha Senhaji, Alan DenAdel, Mahnoor Mirza, Hyun Hwan An, Laura L. Bilal, Peter Dennis, Catharine S. Leahy, Kay Shigemori, Jennyfer Galves-Reyes, Ye Zhang, Foster Powers, Nolawit Mulugeta, Alejandro J. Gupta, Nicholas L. Calistri, Alexandria van Scoyk, Kristen Jones, Huiyun Liu, Kristen Stevenson, S. Ren, M. Luskin, Charles P. Couturier, Ava P. Amini, Srivatsan Raghavan, Robert J. Kimmerling, Mark M. Stevens, Lorin Crawford, David M. Weinstock, Scott R. Manalis, Alex K. Shalek, Mark A. Murakami
  
  bioRxiv | June 2024
  
  Preprint
- A knockoff calibration method to avoid over-clustering in single-cell RNA-sequencing
  
  Alan DenAdel, Michelle L. Ramseier, Andrew W. Navia, Alex K. Shalek, Srivatsan Raghavan, Peter S. Winter, Ava P. Amini, Lorin Crawford
  
  bioRxiv | March 2024
  
  Preprint
- Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data
  
  Chibuikem Nwizu, Madeline Hughes, Michelle L. Ramseier, Andrew W. Navia, Alex K. Shalek, Nicolo Fusi, Srivatsan Raghavan, Peter S. Winter, Ava P. Amini, Lorin Crawford
  
  bioRxiv | February 2024
  
  Preprint
- Microenvironment drives cell state, plasticity, and drug response in pancreatic cancer
  
  Srivatsan Raghavan, Peter S. Winter, Andrew W Navia, Hannah L. Williams, Alan DenAdel, Kristen E. Lowder, Jennyfer Galvez-Reyes, R. Kalekar, Nolawit Mulugeta, Kevin S. Kapner, M. Raghavan, Ashir A. Borah, Nuo Liu, Sara A. Väyrynen, Andressa Dias Costa, R. Ng, Junning Wang, Emma K. Hill, Dorisanne Y. Ragon, L. Brais, Alex M. Jaeger, Liam F. Spurr, Yvonne Y. Li, A. Cherniack, M. Booker, Elizabeth F Cohen, M. Tolstorukov, Isaac Wakiro, Asaf Rotem, B. Johnson, James M. McFarland, E. Sicinska, T. Jacks, R. Sullivan, G. Shapiro, T. Clancy, Kimberly Perez, D. Rubinson, K. Ng, J. Cleary, Lorin Crawford, S. Manalis, J. Nowak, B. Wolpin, William C. Hahn, A. Aguirre, A. Shalek
  
  PubMed Cell | November 2021, 第 184 卷: pp. 6119-6137.e26
  
  DOI Publication Publication
- Assessing the limits of zero-shot foundation models in single-cell biology
  
  Kasia Z. Kedzierska, Lorin Crawford, Ava P. Amini, Alex Lu
  
  bioRxiv | November 2023
  
  Preprint PDF

- Consequences of training data composition for deep learning models in single-cell biology
  
  Ajay Nadig, Akshaya Thoutam, Madeline Hughes, Anay Gupta, Andrew W. Navia, Nicolo Fusi, Srivatsan Raghavan, Peter S. Winter, Ava P. Amini, Lorin Crawford
  
  bioRxiv | February 2025
  
  Publication DOI
- Evaluating the role of pre-training dataset size and diversity on single-cell foundation model performance
  
  Alan DenAdel, Madeline Hughes, Akshaya Thoutam, Anay Gupta, Nicolo Fusi, Andrew W. Navia, Srivatsan Raghavan, Peter S. Winter, Ava P. Amini, Lorin Crawford
  
  bioRxiv | December 2024
  
  Preprint
- Scalable, compressed phenotypic screening using pooled perturbations.
  
  Nuo Liu, Walaa E. Kattan, Benjamin E. Mead, Conner Kummerlowe, Thomas Cheng, Sarah Ingabire, Jaime H Cheah, Christian K Soule, Anita Vrcic, Jane K. McIninch, Sergio Triana, Manuel Guzman, Tyler T. Dao, Joshua M. Peters, Kristen E. Lowder, Lorin Crawford, Ava P. Amini, Paul C. Blainey, William C. Hahn, Brian Cleary, Bryan D. Bryson, Peter S. Winter, Srivatsan Raghavan, Alex K. Shalek
  
  Nature biotechnology | October 2024
  
  DOI Publication
- Mutation and cell state compatibility is required and targetable in Ph+ acute lymphoblastic leukemia minimal residual disease
  
  Peter S. Winter, Michelle L. Ramseier, Andrew W. Navia, Sachit D. Saksena, Haley Strouf, Nezha Senhaji, Alan DenAdel, Mahnoor Mirza, Hyun Hwan An, Laura L. Bilal, Peter Dennis, Catharine S. Leahy, Kay Shigemori, Jennyfer Galves-Reyes, Ye Zhang, Foster Powers, Nolawit Mulugeta, Alejandro J. Gupta, Nicholas L. Calistri, Alexandria van Scoyk, Kristen Jones, Huiyun Liu, Kristen Stevenson, S. Ren, M. Luskin, Charles P. Couturier, Ava P. Amini, Srivatsan Raghavan, Robert J. Kimmerling, Mark M. Stevens, Lorin Crawford, David M. Weinstock, Scott R. Manalis, Alex K. Shalek, Mark A. Murakami
  
  bioRxiv | June 2024
  
  Preprint
- A knockoff calibration method to avoid over-clustering in single-cell RNA-sequencing
  
  Alan DenAdel, Michelle L. Ramseier, Andrew W. Navia, Alex K. Shalek, Srivatsan Raghavan, Peter S. Winter, Ava P. Amini, Lorin Crawford
  
  bioRxiv | March 2024
  
  Preprint
- Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data
  
  Chibuikem Nwizu, Madeline Hughes, Michelle L. Ramseier, Andrew W. Navia, Alex K. Shalek, Nicolo Fusi, Srivatsan Raghavan, Peter S. Winter, Ava P. Amini, Lorin Crawford
  
  bioRxiv | February 2024
  
  Preprint
- Assessing the limits of zero-shot foundation models in single-cell biology
  
  Kasia Z. Kedzierska, Lorin Crawford, Ava P. Amini, Alex Lu
  
  bioRxiv | November 2023
  
  Preprint PDF
- Microenvironment drives cell state, plasticity, and drug response in pancreatic cancer
  
  Srivatsan Raghavan, Peter S. Winter, Andrew W Navia, Hannah L. Williams, Alan DenAdel, Kristen E. Lowder, Jennyfer Galvez-Reyes, R. Kalekar, Nolawit Mulugeta, Kevin S. Kapner, M. Raghavan, Ashir A. Borah, Nuo Liu, Sara A. Väyrynen, Andressa Dias Costa, R. Ng, Junning Wang, Emma K. Hill, Dorisanne Y. Ragon, L. Brais, Alex M. Jaeger, Liam F. Spurr, Yvonne Y. Li, A. Cherniack, M. Booker, Elizabeth F Cohen, M. Tolstorukov, Isaac Wakiro, Asaf Rotem, B. Johnson, James M. McFarland, E. Sicinska, T. Jacks, R. Sullivan, G. Shapiro, T. Clancy, Kimberly Perez, D. Rubinson, K. Ng, J. Cleary, Lorin Crawford, S. Manalis, J. Nowak, B. Wolpin, William C. Hahn, A. Aguirre, A. Shalek
  
  PubMed Cell | November 2021, 第 184 卷: pp. 6119-6137.e26
  
  DOI Publication Publication

Project Ex Vivo

论文与出版物

Consequences of training data composition for deep learning models in single-cell biology

Evaluating the role of pre-training dataset size and diversity on single-cell foundation model performance

Scalable, compressed phenotypic screening using pooled perturbations.

Mutation and cell state compatibility is required and targetable in Ph+ acute lymphoblastic leukemia minimal residual disease

A knockoff calibration method to avoid over-clustering in single-cell RNA-sequencing

Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data

Assessing the limits of zero-shot foundation models in single-cell biology

Microenvironment drives cell state, plasticity, and drug response in pancreatic cancer

Consequences of training data composition for deep learning models in single-cell biology

Evaluating the role of pre-training dataset size and diversity on single-cell foundation model performance

Scalable, compressed phenotypic screening using pooled perturbations.

Mutation and cell state compatibility is required and targetable in Ph+ acute lymphoblastic leukemia minimal residual disease

A knockoff calibration method to avoid over-clustering in single-cell RNA-sequencing

Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data

Microenvironment drives cell state, plasticity, and drug response in pancreatic cancer

Assessing the limits of zero-shot foundation models in single-cell biology

Consequences of training data composition for deep learning models in single-cell biology

Evaluating the role of pre-training dataset size and diversity on single-cell foundation model performance

Scalable, compressed phenotypic screening using pooled perturbations.

Mutation and cell state compatibility is required and targetable in Ph+ acute lymphoblastic leukemia minimal residual disease

A knockoff calibration method to avoid over-clustering in single-cell RNA-sequencing

Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data

Assessing the limits of zero-shot foundation models in single-cell biology

Microenvironment drives cell state, plasticity, and drug response in pancreatic cancer