Joe W. Gray

Molecular Biology · 2000–2020

A researcher in the Science corpus: 25 papers; trusts 14 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 300 citations into it; #7,596 of 17,773 by trust here, #491 by citations
• Oncology — 99 citations into it
• Artificial Intelligence — 50 citations into it
• Pathology and Forensic Medicine — 50 citations into it
• Statistics and Probability — 30 citations into it; #7,391 of 12,932 by trust here, #8,279 by citations
• Causal Inference & Discovery — 9 citations into it
• Cell Biology — 8 citations into it
• Probabilistic & Bayesian Methods — 8 citations into it

Whom Joe W. Gray trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Inderjit S. Dhillon
2. Gitta Kutyniok
3. D. Sidransky
4. Judea Pearl
5. Scott Shaobing Chen
6. Fan Li
7. Yuval Kluger
8. Seung-Jean Kim
9. Robert Tibshirani
10. Daniel Eaton

Who trusts Joe W. Gray overall

1. Yu Zhang
2. Qiang Yang
3. Aurelie C. Lozano

Papers from Joe W. Gray's perspective

Ordered by how strongly the researchers Joe W. Gray trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet: A large-scale hierarchical image database
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Atomic Decomposition by Basis Pursuit
10. Random Forests

Their papers

• An integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR and NF1 (2010) — 7,152 citations
• Induction of Tumors in Mice by Genomic Hypomethylation (2003) — 1,424 citations
• A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. (2006) — 3,249 citations
• Chromosome aberrations in solid tumors (2003) — 859 citations
• Inferring causal molecular networks: empirical assessment through a community-based effort (2016) — 222 citations
• Assembly of microarrays for genome-wide measurement of DNA copy number (2001) — 1,027 citations
• Integrated Genomic Analyses of Ovarian Carcinoma (2011) — 7,559 citations
• Comprehensive genomic characterization defines human glioblastoma genes and core pathways (2008) — 7,050 citations
• Causal network inference using biochemical kinetics (2014) — 60 citations
• An Integrative Genomic and Proteomic Analysis of PIK3CA, PTEN, and AKT Mutations in Breast Cancer (2008) — 1,067 citations
• The Library of Integrated Network-based Cellular Signatures (LINCS) NIH Program: System-level Cataloging of Human Cells Response to Perturbations (2017) — 380 citations
• The genetics and genomics of cancer (2003) — 623 citations
• Prognostically relevant gene signatures of high-grade serous ovarian carcinoma. (2012) — 595 citations
• A community effort to assess and improve drug sensitivity prediction algorithms (2014) — 728 citations
• Sparse multitask regression for identifying common mechanism of response to therapeutic targets (2010) — 63 citations
• The morphologies of breast cancer cell lines in three‐dimensional assays correlate with their profiles of gene expression (2007) — 1,078 citations
• Joint estimation of multiple networks from time course data (2013) — 20 citations
• How Machine Learning will Transform Biomedicine (2020) — 480 citations
• The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution (2020) — 482 citations
• The Consensus Molecular Subtypes of Colorectal Cancer (2015) — 4,640 citations