Mark A. Dane
Oregon Health & Science University
30 Papers
12 Citations
Mark A. Dane is an academic researcher from Oregon Health & Science University. The author has contributed to research in topics: Biology & Medicine. The author has an hindex of 6, co-authored 17 publications.
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Papers
The Library of Integrated Network-Based Cellular Signatures NIH Program: System-Level Cataloging of Human Cells Response to Perturbations
Alexandra B Keenan,Sherry L. Jenkins,Kathleen M. Jagodnik,Simon Koplev,Edward He,Denis Torre,Zichen Wang,Anders B. Dohlman,Moshe C. Silverstein,Alexander Lachmann,Maxim V. Kuleshov,Avi Ma'ayan,Vasileios Stathias,Raymond Terryn,Daniel J. Cooper,Michele Forlin,Amar Koleti,Dusica Vidovic,Caty Chung,Stephan C. Schürer,Jouzas Vasiliauskas,Marcin Pilarczyk,Behrouz Shamsaei,Mehdi Fazel,Yan Ren,Wen Niu,Nicholas A. Clark,Shana White,Naim Al Mahi,Lixia Zhang,Michal Kouril,John F. Reichard,Siva Sivaganesan,Mario Medvedovic,Jaroslaw Meller,Rick J. Koch,Marc R. Birtwistle,Ravi Iyengar,Eric A. Sobie,Evren U. Azeloglu,Julia A. Kaye,Jeannette Osterloh,Kelly Haston,Jaslin Kalra,Steve Finkbiener,Jonathan Z. Li,Pamela Milani,Miriam Adam,Renan Escalante-Chong,Karen Sachs,Alexander LeNail,Divya Ramamoorthy,Ernest Fraenkel,Gavin Daigle,Uzma Hussain,Alyssa Coye,Jeffrey D. Rothstein,Dhruv Sareen,Loren Ornelas,Maria G. Banuelos,Berhan Mandefro,Ritchie Ho,Clive N. Svendsen,Ryan G. Lim,Jennifer Stocksdale,Malcolm Casale,Terri G. Thompson,Jie Wu,Leslie M. Thompson,Victoria Dardov,Vidya Venkatraman,Andrea Matlock,Jennifer E. Van Eyk,Jacob D. Jaffe,Malvina Papanastasiou,Aravind Subramanian,Todd R. Golub,Sean D. Erickson,Mohammad Fallahi-Sichani,Marc Hafner,Nathanael S. Gray,Jia-Ren Lin,Caitlin E. Mills,Jeremy L. Muhlich,Mario Niepel,Caroline E. Shamu,Elizabeth H. Williams,David Wrobel,Peter K. Sorger,Laura M. Heiser,Joe W. Gray,James E. Korkola,Gordon B. Mills,Mark A. LaBarge,Mark A. LaBarge,Heidi S. Feiler,Mark A. Dane,Elmar Bucher,Michel Nederlof,Damir Sudar,Sean M. Gross,David Kilburn,Rebecca Smith,Kaylyn Devlin,Ron Margolis,Leslie Derr,Albert Lee,Ajay Pillai +107 more
TL;DR: The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders.
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A multi-encoder variational autoencoder controls multiple transformational features in single-cell image analysis
Luke Ternes,Mark A. Dane,Sean M. Gross,Marilyne Labrie,Joe W. Gray,Laura M. Heiser,Young Hwan Chang +6 more
TL;DR: In this article , a multi-encoder VAE (ME-VAE) was proposed for single cell image analysis using transformed images as a self-supervised signal to extract transform-invariant biologically meaningful features.
Individual Cells Can Resolve Variations in Stimulus Intensity along the IGF-PI3K-AKT Signaling Axis.
TL;DR: The rational development of a genetically encoded FoxO1 sensor is described, which serves as a down-stream readout of insulin growth factor-phosphatidylinositol 3-kinase IGF-PI3K-AKT signaling pathway activity, and these responses are sustained over time, reproducible at the single-cell level, and display cell-to-cell heterogeneity.
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Genome co-amplification upregulates a mitotic gene network activity that predicts outcome and response to mitotic protein inhibitors in breast cancer.
Zhi Hu,Jian-Hua Mao,Christina Curtis,Ge Huang,Shenda Gu,Laura M. Heiser,Marc E. Lenburg,James E. Korkola,Nora Bayani,Shamith A. Samarajiwa,Jose A. Seoane,Mark A. Dane,Amanda Esch,Heidi S. Feiler,Nicholas J. Wang,Mary Ann Hardwicke,Sylvie Laquerre,Jeff Jackson,Kenneth Wood,Barbara L. Weber,Paul T. Spellman,Samuel Aparicio,Richard Wooster,Carlos Caldas,Joe W. Gray +24 more
TL;DR: A molecular signature which may guide therapeutic approaches for tumors with high mitotic network activity is defined and 22 genes that might be considered as additional therapeutic targets for this clinically relevant patient subgroup are identified.
Analysis and modeling of cancer drug responses using cell cycle phase-specific rate effects
Sean M. Gross,Farnaz Yar Mohammadi,Crystal Sanchez-Aguila,Paulina J. Zhan,Tiera Liby,Mark A. Dane,Aaron S. Meyer,Laura M. Heiser +7 more
TL;DR: In this paper , a linear chain trick (LCT) computational model was used to capture drug-induced dynamic responses, correctly infers drug effects, and reproduces influences on specific cell cycle phases.
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