Lorin Crawford

Principal Researcher

出版物

表示方法:

- 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 プロジェクト
- 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 プロジェクト
- 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 プロジェクト
- 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 プロジェクト
- 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 プロジェクト
- 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 プロジェクト
- 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 プロジェクト
- Multioviz: an interactive platform for in silico perturbation and interrogation of gene regulatory networks
  
  Helen Xie, Lorin Crawford, Ashley Conard
  
  October 2023
  
  DOI Publication
- Deep self-supervised learning for biosynthetic gene cluster detection and product classification
  
  Carolina Rios-Martinez, Nicholas Bhattacharya, Ava P. Amini, Lorin Crawford, Kevin Kaichuang Yang
  
  PLOS Computational Biology | May 2023, 巻19(5)
  
  DOI Publication
- 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, 巻184: pp. 6119-6137.e26
  
  DOI Publication Publication プロジェクト
- 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
- 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, 巻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, 巻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, 巻17(3)
  
  DOI 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, 巻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, 巻16(6): pp. 1139-1150
  
  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
- 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, 巻317(2)
  
  DOI
- Fast and flexible linear mixed models for genome-wide genetics.
  
  Daniel E. Runcie, Lorin Crawford
  
  PLOS Genetics | February 2019, 巻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
- 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, 巻113(524): pp. 1710-1721
  
  DOI
- 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, 巻13(7)
  
  DOI

- 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 プロジェクト
- 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 プロジェクト
- 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 プロジェクト
- 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 プロジェクト
- 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 プロジェクト
- 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 プロジェクト
- Multioviz: an interactive platform for in silico perturbation and interrogation of gene regulatory networks
  
  Helen Xie, Lorin Crawford, Ashley Conard
  
  October 2023
  
  DOI Publication
- Deep self-supervised learning for biosynthetic gene cluster detection and product classification
  
  Carolina Rios-Martinez, Nicholas Bhattacharya, Ava P. Amini, Lorin Crawford, Kevin Kaichuang Yang
  
  PLOS Computational Biology | May 2023, 巻19(5)
  
  DOI Publication
- 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, 巻184: pp. 6119-6137.e26
  
  DOI Publication Publication プロジェクト
- 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
- 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, 巻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, 巻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, 巻17(3)
  
  DOI 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, 巻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, 巻16(6): pp. 1139-1150
  
  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
- 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, 巻317(2)
  
  DOI
- Fast and flexible linear mixed models for genome-wide genetics.
  
  Daniel E. Runcie, Lorin Crawford
  
  PLOS Genetics | February 2019, 巻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
- 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, 巻113(524): pp. 1710-1721
  
  DOI
- 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, 巻13(7)
  
  DOI
- 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 プロジェクト

- 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 プロジェクト
- 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 プロジェクト
- 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 プロジェクト
- 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 プロジェクト
- 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 プロジェクト
- 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 プロジェクト
- 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 プロジェクト
- Deep self-supervised learning for biosynthetic gene cluster detection and product classification
  
  Carolina Rios-Martinez, Nicholas Bhattacharya, Ava P. Amini, Lorin Crawford, Kevin Kaichuang Yang
  
  PLOS Computational Biology | May 2023, 巻19(5)
  
  DOI Publication
- 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, 巻184: pp. 6119-6137.e26
  
  DOI Publication Publication プロジェクト
- 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
- 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, 巻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, 巻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, 巻17(3)
  
  DOI 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, 巻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, 巻16(6): pp. 1139-1150
  
  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
- 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, 巻317(2)
  
  DOI
- Fast and flexible linear mixed models for genome-wide genetics.
  
  Daniel E. Runcie, Lorin Crawford
  
  PLOS Genetics | February 2019, 巻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
- 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, 巻113(524): pp. 1710-1721
  
  DOI
- 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, 巻13(7)
  
  DOI
- Multioviz: an interactive platform for in silico perturbation and interrogation of gene regulatory networks
  
  Helen Xie, Lorin Crawford, Ashley Conard
  
  October 2023
  
  DOI Publication

Lorin Crawford

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

Multioviz: an interactive platform for in silico perturbation and interrogation of gene regulatory networks

Deep self-supervised learning for biosynthetic gene cluster detection and product classification

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

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

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

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

Redefining replication in multi-ancestry genome-wide association studies

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

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

Generalizing Variational Autoencoders with Hierarchical Empirical Bayes.

Multi-scale Genomic Inference using Biologically Annotated Neural Networks

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

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

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

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

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

Interpreting Deep Neural Networks Through Variable Importance.

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

Bayesian Approximate Kernel Regression with Variable Selection

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

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

Multioviz: an interactive platform for in silico perturbation and interrogation of gene regulatory networks

Deep self-supervised learning for biosynthetic gene cluster detection and product classification

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

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

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

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

Redefining replication in multi-ancestry genome-wide association studies

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

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

Generalizing Variational Autoencoders with Hierarchical Empirical Bayes.

Multi-scale Genomic Inference using Biologically Annotated Neural Networks

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

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

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

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

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

Interpreting Deep Neural Networks Through Variable Importance.

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

Bayesian Approximate Kernel Regression with Variable Selection

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

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

Deep self-supervised learning for biosynthetic gene cluster detection and product classification

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

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

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

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

Redefining replication in multi-ancestry genome-wide association studies

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

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

Generalizing Variational Autoencoders with Hierarchical Empirical Bayes.

Multi-scale Genomic Inference using Biologically Annotated Neural Networks

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

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

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

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

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

Interpreting Deep Neural Networks Through Variable Importance.

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