Jump to content

Dana Pe'er

Edit links
From Wikipedia, the free encyclopedia
Dana Pe'er
Dana Pe'er
Born1971 (age 52–53)[2]
Alma materHebrew University of Jerusalem[3]
SpouseItsik Pe'er[4]
ChildrenInbar, Carmel[5][6]
Awards
Scientific career
FieldsBiology
Computational biology
Systems biology
InstitutionsHarvard Medical School
Columbia University
Memorial Sloan Kettering Cancer Center
ThesisFrom Gene Expression to Molecular Pathways (2003)
Doctoral advisorNir Friedman
Other academic advisorsGeorge M. Church

Dana Pe'er (born 1971), Chair and Professor in Computational and Systems Biology Program at Sloan Kettering Institute is a researcher in computational systems biology. A Howard Hughes Medical Institute (HHMI) Investigator since 2021, she was previously a professor at Columbia Department of Biological Sciences. Pe'er's research focuses on understanding the organization, function and evolution of molecular networks, particularly how genetic variations alter the regulatory network and how these genetic variations can cause cancer.

Early life and education

[edit]

Pe'er was born in Israel.[7] Her husband, Itsik Pe'er, is a computational biologist at Columbia University. Together, they have raised two daughters.[4]

Pe'er received a bachelor's degree in mathematics in 1995, as well as master's in 1999 and PhD degrees in computer science in 2003, from the Hebrew University of Jerusalem. She earned her master's degree under Avi Widgerson, and carried out her PhD research in the lab of Nir Friedman.[8][9][10]

She subsequently performed postdoctoral work with George Church at Harvard.[8][9][10] Her fellowship focused on how genetic variation changes the regulatory network between individuals and how this subsequently manifests in phenotypic diversity.[11][12][13]

Career

[edit]

In 2006, Pe'er established a research group in the Department of Biological Sciences and Systems Biology at Columbia University. Pe'er's group at Columbia developed computational methods that combine diverse sources of high throughput genomics data, with the aim of developing a holistic view of the cell at a systems level.[14]

In 2016, Pe'er joined the Sloan Kettering Institute in New York City.[15] While at Sloan, Pe'er was selected as a Howard Hughes Medical Institute (HHMI) Investigator in September, 2021.[16]

Pe'er is also involved in the Human Cell Atlas as a member of the organizing committee, co-chair of the Analysis Working Group, and member of the Human Lung Cell Atlas initiative, and serves on the scientific advisory board of scverse.[17]

Research

[edit]

In her PhD work, Pe'er demonstrated that Bayesian networks can describe interactions between thousands of genes, enabling the analysis of data from newly available DNA microarrays, which generate thousands of noisy measurements of gene expression.[18] The approach has been widely applied to genome-scale sequencing data. In her postdoctoral work, she used this framework to study protein signaling networks in multivariate flow cytometry data.[19]

At Columbia, Pe'er applied Bayesian networks to integrate different data types for the study of gene regulatory networks, determining how DNA sequence variation alters the regulation of gene expression, with a view towards personalized medicine.[20]

The Pe'er research group has developed a series of methods for high-throughput single-cell data analysis, initially to address a new high-dimensional data type derived from mass cytometry, which quantifies a few dozen proteins per cell for millions of cells at a time. They introduced the application of non-linear dimensionality reduction by t-distributed stochastic neighbor embedding (t-SNE) to visualize high-dimensional single-cell RNA sequencing data,[21] and the use of a nearest neighbors graph to represent the data manifold of RNA-defined cell states.[22] The Pe'er group used this formalization to identify discrete cell types or cell states by applying the Louvain community detection method to cluster data,[23] and demonstrated that cells can be ordered along differentiation trajectories from individual samples, due to the asynchrony of cells found in tissue samples.[22] By modeling trajectories as a Markov process, they showed that cells can be assigned probabilities for reaching any given terminal fate along a trajectory.[24] In 2020, the Pe'er and Fabian Theis groups presented CellRank, an algorithm that uncovers cellular dynamics by combining trajectories based on cell-cell similarity with local RNA velocity information, which identifies nascent transcriptional states by the proportion of spliced-to-unspliced RNA transcripts.[25]

Pe'er applies these methods to model biological questions around cellular plasticity and single-cell phenotypic variation in cancer, developmental biology, and immunology, including tumor microenvironments,[26] metastasis[26] and responses to treatments such as immunotherapy. "We are beginning to understand that plasticity is a key hallmark of cancer," said Dr. Pe'er. "It is the cancer cell's plasticity that allows it to make such a switch to survive."

Upon accepting the International Society for Computational Biology's Overton Prize in 2014, Pe'er said, "Math is rigorous, and biology is messy, so the trick is to find the pattern in the mess, and machine learning provides a powerful toolbox."[13]

Selected publications

[edit]
  • Friedman, Nir; Linial, Michal; Nachman, Iftach; Pe'Er, Dana (2000). "Using Bayesian Networks to Analyze Expression Data". Journal of Computational Biology. 7 (3–4): 601–620. doi:10.1089/106652700750050961. PMID 11108481.
  • Sachs, Karen; Perez, Omar; Pe'Er, Dana; Lauffenburger, Douglas A.; Nolan, Garry P. (2005). "Causal Protein-Signaling Networks Derived from Multiparameter Single-Cell Data". Science. 308 (5721): 523–529. Bibcode:2005Sci...308..523S. doi:10.1126/science.1105809. PMID 15845847. S2CID 8160280.
  • Bendall, Sean C.; Davis, Kara L.; Amir, El-ad David; Tadmor, Michelle D.; Simonds, Erin F.; Chen, Tiffany J.; Shenfeld, Daniel K.; Nolan, Garry P.; Pe'Er, Dana (2014). "Single-Cell Trajectory Detection Uncovers Progression and Regulatory Coordination in Human B Cell Development". Cell. 157 (3): 714–725. doi:10.1016/j.cell.2014.04.005. PMC 4045247. PMID 24766814.
  • Levine, Jacob H.; Simonds, Erin F.; Bendall, Sean C.; Davis, Kara L.; Amir, El-ad D.; Tadmor, Michelle D.; Litvin, Oren; Fienberg, Harris G.; Jager, Astraea; Zunder, Eli R.; Finck, Rachel; Gedman, Amanda L.; Radtke, Ina; Downing, James R.; Pe'Er, Dana; Nolan, Garry P. (2015). "Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis". Cell. 162 (1): 184–197. doi:10.1016/j.cell.2015.05.047. PMC 4508757. PMID 26095251. S2CID 11608684.
  • Azizi, Elham; Carr, Ambrose J.; Plitas, George; Cornish, Andrew E.; Konopacki, Catherine; Prabhakaran, Sandhya; Nainys, Juozas; Wu, Kenmin; Kiseliovas, Vaidotas; Setty, Manu; Choi, Kristy; Fromme, Rachel M.; Dao, Phuong; McKenney, Peter T.; Wasti, Ruby C.; Kadaveru, Krishna; Mazutis, Linas; Rudensky, Alexander Y.; Pe'Er, Dana (2018). "Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment". Cell. 174 (5): 1293–1308.e36. doi:10.1016/j.cell.2018.05.060. PMC 6348010. PMID 29961579.
  • Nowotschin, Sonja; Setty, Manu; Kuo, Ying-Yi; Liu, Vincent; Garg, Vidur; Sharma, Roshan; Simon, Claire S.; Saiz, Nestor; Gardner, Rui; Boutet, Stéphane C.; Church, Deanna M.; Hoodless, Pamela A.; Hadjantonakis, Anna-Katerina; Pe'Er, Dana (2019). "The emergent landscape of the mouse gut endoderm at single-cell resolution". Nature. 569 (7756): 361–367. Bibcode:2019Natur.569..361N. doi:10.1038/s41586-019-1127-1. PMC 6724221. PMID 30959515.
  • Laughney, Ashley M.; Hu, Jing; Campbell, Nathaniel R.; Bakhoum, Samuel F.; Setty, Manu; Lavallée, Vincent-Philippe; Xie, Yubin; Masilionis, Ignas; Carr, Ambrose J.; Kottapalli, Sanjay; Allaj, Viola; Mattar, Marissa; Rekhtman, Natasha; Xavier, Joao B.; Mazutis, Linas; Poirier, John T.; Rudin, Charles M.; Pe'Er, Dana; Massagué, Joan (2020). "Regenerative lineages and immune-mediated pruning in lung cancer metastasis". Nature Medicine. 26 (2): 259–269. doi:10.1038/s41591-019-0750-6. PMC 7021003. PMID 32042191.
  • Friedman, N.; Linial, M.; Nachman, I.; Pe'er, D. (2000). "Using Bayesian Networks to Analyze Expression Data". Journal of Computational Biology. 7 (3–4): 601–620. CiteSeerX 10.1.1.191.139. doi:10.1089/106652700750050961. PMID 11108481.
  • Segal, E.; Shapira, M.; Regev, A.; Pe'er, D.; Botstein, D.; Koller, D.; Friedman, N. (2003). "Module networks: Identifying regulatory modules and their condition-specific regulators from gene expression data". Nature Genetics. 34 (2): 166–176. doi:10.1038/ng1165. PMID 12740579. S2CID 6146032.
  • Sachs, K.; Perez, O; Pe'Er, D; Lauffenburger, D. A.; Nolan, G. P. (2005). "Causal Protein-Signaling Networks Derived from Multiparameter Single-Cell Data". Science. 308 (5721): 523–9. Bibcode:2005Sci...308..523S. doi:10.1126/science.1105809. PMID 15845847. S2CID 8160280.
  • Bendall, S. C.; Simonds, E. F.; Qiu, P.; Amir, E. -A. D.; Krutzik, P. O.; Finck, R.; Bruggner, R. V.; Melamed, R.; Trejo, A.; Ornatsky, O. I.; Balderas, R. S.; Plevritis, S. K.; Sachs, K.; Pe'Er, D.; Tanner, S. D.; Nolan, G. P. (2011). "Single-Cell Mass Cytometry of Differential Immune and Drug Responses Across a Human Hematopoietic Continuum". Science. 332 (6030): 687–696. Bibcode:2011Sci...332..687B. doi:10.1126/science.1198704. PMC 3273988. PMID 21551058.

Memberships

[edit]

Awards

[edit]

References

[edit]
  1. ^ Fogg, Christiana N.; Kovats, Diane E. (2014). "International Society for Computational Biology Honors Dana Pe'er with Top Bioinformatics/Computational Biology Award for 2014". PLOS Computational Biology. 10 (6): e1003682. Bibcode:2014PLSCB..10E3682F. doi:10.1371/journal.pcbi.1003682. PMC 4063598. PMID 24945496.
  2. ^ "98109969".
  3. ^ "Dana Pe'er - HomePage". Archived from the original on 29 June 2010. Retrieved 8 February 2014.
  4. ^ a b c Oh, Clare (September 20, 2007). "Columbia News". Columbia News. Archived from the original on February 23, 2014. Retrieved 2023-04-20.
  5. ^ "TEDxYouth@TheSchool - The Spark! - TEDx - TED.com". www.ted.com. Retrieved 8 February 2014.
  6. ^ "Dana Pe'er - Genealogy". www.geni.com. Retrieved 19 July 2014.
  7. ^ Ronel, Asaf (September 29, 2019). "A Project to Map All Human Cells Will Change How Disease Is Cured". Haaretz. Retrieved 2023-03-22.
  8. ^ a b "2011 Innovative Research Grants Investigator Biographies". www.aacr.org. Archived from the original on 22 February 2014. Retrieved 9 February 2014.
  9. ^ a b "Dana Pe'er - Dissertation". Archived from the original on 28 October 2014. Retrieved 9 February 2014.
  10. ^ a b Lee, S. I.; Pe'Er, D; Dudley, A. M.; Church, G. M.; Koller, D (2006). "Identifying regulatory mechanisms using individual variation reveals key role for chromatin modification". Proceedings of the National Academy of Sciences. 103 (38): 14062–7. Bibcode:2006PNAS..10314062L. doi:10.1073/pnas.0601852103. PMC 1599912. PMID 16968785.
  11. ^ Lee, S. I.; Pe'Er, D; Dudley, A. M.; Church, G. M.; Koller, D (2006). "Identifying regulatory mechanisms using individual variation reveals key role for chromatin modification". Proceedings of the National Academy of Sciences. 103 (38): 14062–7. Bibcode:2006PNAS..10314062L. doi:10.1073/pnas.0601852103. PMC 1599912. PMID 16968785.
  12. ^ "GET :: Genomes Environments Traits". www.getconference.org. Retrieved 8 February 2014.
  13. ^ a b "2011 Innovative Research Grants Investigator Biographies". www.aacr.org. Archived from the original on 22 February 2014. Retrieved 9 February 2014.
  14. ^ "Center for Computational Biology and Bioinformatics (C2B2) | Columbia University Department of Systems Biology". systemsbiology.columbia.edu. Retrieved 2023-02-14.
  15. ^ "Notable Women in Healthcare - Dana Pe'er". Crain's New York Business. 2019-08-02. Retrieved 2023-02-14.
  16. ^ "HHMI Invests $300 Million in 33 New Investigators". HHMI. Retrieved 2023-02-14.
  17. ^ "Hello world". scverse.org. 2022-05-17. Retrieved 2023-02-14.
  18. ^ Friedman, N.; Linial, M.; Nachman, I.; Pe'er, D. (2000). "Using Bayesian networks to analyze expression data". Journal of Computational Biology: A Journal of Computational Molecular Cell Biology. 7 (3–4): 601–620. doi:10.1089/106652700750050961. ISSN 1066-5277. PMID 11108481.
  19. ^ Sachs, Karen; Perez, Omar; Pe'er, Dana; Lauffenburger, Douglas A.; Nolan, Garry P. (2005-04-22). "Causal protein-signaling networks derived from multiparameter single-cell data". Science. 308 (5721): 523–529. Bibcode:2005Sci...308..523S. doi:10.1126/science.1105809. ISSN 1095-9203. PMID 15845847. S2CID 8160280.
  20. ^ Sanchez-Garcia, Félix; Villagrasa, Patricia; Matsui, Junji; Kotliar, Dylan; Castro, Verónica; Akavia, Uri-David; Chen, Bo-Juen; Saucedo-Cuevas, Laura; Rodriguez Barrueco, Ruth; Llobet-Navas, David; Silva, Jose M.; Pe'er, Dana (2014-12-04). "Integration of genomic data enables selective discovery of breast cancer drivers". Cell. 159 (6): 1461–1475. doi:10.1016/j.cell.2014.10.048. ISSN 1097-4172. PMC 4258423. PMID 25433701.
  21. ^ Amir, El-ad David; Davis, Kara L.; Tadmor, Michelle D.; Simonds, Erin F.; Levine, Jacob H.; Bendall, Sean C.; Shenfeld, Daniel K.; Krishnaswamy, Smita; Nolan, Garry P.; Pe'er, Dana (June 2013). "viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia". Nature Biotechnology. 31 (6): 545–552. doi:10.1038/nbt.2594. ISSN 1546-1696. PMC 4076922. PMID 23685480.
  22. ^ a b Bendall, Sean C.; Davis, Kara L.; Amir, El-Ad David; Tadmor, Michelle D.; Simonds, Erin F.; Chen, Tiffany J.; Shenfeld, Daniel K.; Nolan, Garry P.; Pe'er, Dana (2014-04-24). "Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development". Cell. 157 (3): 714–725. doi:10.1016/j.cell.2014.04.005. ISSN 1097-4172. PMC 4045247. PMID 24766814.
  23. ^ Levine, Jacob H.; Simonds, Erin F.; Bendall, Sean C.; Davis, Kara L.; Amir, El-ad D.; Tadmor, Michelle D.; Litvin, Oren; Fienberg, Harris G.; Jager, Astraea; Zunder, Eli R.; Finck, Rachel; Gedman, Amanda L.; Radtke, Ina; Downing, James R.; Pe'er, Dana (2015-07-02). "Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis". Cell. 162 (1): 184–197. doi:10.1016/j.cell.2015.05.047. ISSN 1097-4172. PMC 4508757. PMID 26095251.
  24. ^ Setty, Manu; Kiseliovas, Vaidotas; Levine, Jacob; Gayoso, Adam; Mazutis, Linas; Pe'er, Dana (April 2019). "Characterization of cell fate probabilities in single-cell data with Palantir". Nature Biotechnology. 37 (4): 451–460. doi:10.1038/s41587-019-0068-4. ISSN 1546-1696. PMC 7549125. PMID 30899105.
  25. ^ Lange, Marius; Bergen, Volker; Klein, Michal; Setty, Manu; Reuter, Bernhard; Bakhti, Mostafa; Lickert, Heiko; Ansari, Meshal; Schniering, Janine; Schiller, Herbert B.; Pe'er, Dana; Theis, Fabian J. (February 2022). "CellRank for directed single-cell fate mapping". Nature Methods. 19 (2): 159–170. doi:10.1038/s41592-021-01346-6. ISSN 1548-7105. PMC 8828480. PMID 35027767.
  26. ^ a b Nowotschin, Sonja; Setty, Manu; Kuo, Ying-Yi; Liu, Vincent; Garg, Vidur; Sharma, Roshan; Simon, Claire S.; Saiz, Nestor; Gardner, Rui; Boutet, Stéphane C.; Church, Deanna M.; Hoodless, Pamela A.; Hadjantonakis, Anna-Katerina; Pe'er, Dana (May 2019). "The emergent landscape of the mouse gut endoderm at single-cell resolution". Nature. 569 (7756): 361–367. Bibcode:2019Natur.569..361N. doi:10.1038/s41586-019-1127-1. ISSN 1476-4687. PMC 6724221. PMID 30959515.
  27. ^ "Editorial board: Cell". www.cell.com. Retrieved 18 January 2022.
  28. ^ "Governance". www.humancellatlas.org. Retrieved 2022-12-05.
  29. ^ "Scientific Advisory Committee – EMBL Council". Retrieved 2022-12-05.
  30. ^ "About Us". EPFL. Retrieved 2022-12-05.
  31. ^ "Program Details". pew.org. Retrieved 2022-12-05.
  32. ^ "March 02, 2021: ISCB Congratulates and Introduces the 2021 Class of Fellows!". www.iscb.org. Retrieved 17 June 2022.
  33. ^ "HHMI Invests $300 Million in 33 New Investigators". HHMI. Retrieved 2021-09-23.
  34. ^ "AACR Announces Fellows of the AACR Academy Class of 2023 and New AACR Academy President". American Association for Cancer Research (AACR). Retrieved 2024-04-01.
  35. ^ "Notable Women in Healthcare 2019". Crain's New York Business. 2019-07-23. Retrieved 2022-12-05.
  36. ^ "Sloan Kettering Institute's Dana Pe'er Named Howard Hughes Medical Institute Investigator | Memorial Sloan Kettering Cancer Center". www.mskcc.org. 23 September 2021. Retrieved 2022-12-05.
  37. ^ "NIH Director's Pioneer Award Program - 2014 Award Recipients". commonfund.nih.gov. 2018-09-18. Retrieved 2022-12-05.
  38. ^ "Jan 24, 2014: Gene Myers and Dana Pe'er Named 2014 ISCB Award Winners". www.iscb.org. ISCB. Retrieved 8 February 2014.
  39. ^ "RECOMB Awards". RECOMB Conference Series. Retrieved 2022-12-05.
  40. ^ "Stand Up To Cancer awards next round of Innovative Research Grants - Dana-Farber Cancer Institute | Boston, MA". www.dana-farber.org. Retrieved 2022-12-05.
  41. ^ "Dana Pe'er - Packard Foundation". www.packard.org. Retrieved 8 February 2014.
  42. ^ "Sloan Kettering Institute's Dana Pe'er named Howard Hughes Medical Institute Investigator". EurekAlert!. Retrieved 2022-12-05.
  43. ^ "ISCB Innovator Award". www.iscb.org. Retrieved 2024-04-01.
[edit]
Retrieved from "https://en.wikipedia.org/w/index.php?title=Dana_Pe%27er&oldid=1216804956"