Ron Shamir

Molecular Biology · 2000–2018

A researcher in the Science corpus: 16 papers; trusts 125 researchers and is trusted by 50 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 194 citations into it; #1,385 of 17,773 by trust here, #3,408 by citations
• Artificial Intelligence — 26 citations into it; #7,582 of 35,345 by trust here, #16,771 by citations
• Genetics — 17 citations into it
• Computational Theory and Mathematics — 13 citations into it
• Biomedical Engineering — 12 citations into it
• Computer Vision and Pattern Recognition — 12 citations into it
• Probabilistic & Bayesian Methods — 10 citations into it
• Plant Science — 9 citations into it

Whom Ron Shamir trusts overall

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

1. Roded Sharan
2. Judea Pearl
3. Daniel T. Gillespie
4. Geoffrey E. Hinton
5. Michel X. Goemans
6. Ilya Sutskever
7. Moses Charikar
8. Ulrike von Luxburg
9. Peter J. Rousseeuw
10. Virginia de Sa

Who trusts Ron Shamir overall

1. Roded Sharan
2. Igor Ulitsky
3. Natasa Przulj
4. Rui Xu
5. Dongkuan Xu
6. Bonnie Berger
7. David L. Levy
8. Adi Maron-Katz
9. Doulaye Dembélé
10. D. Bassett

Papers from Ron Shamir's perspective

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

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

Their papers

• Network-based prediction of protein function (2007) — 1,086 citations
• Multi-omic and multi-view clustering algorithms: review and cancer benchmark (2018) — 440 citations
• Revealing modularity and organization in the yeast molecular network by integrated analysis of highly heterogeneous genomewide data. (2004) — 429 citations
• Genome-wide in silico identification of transcriptional regulators controlling the cell cycle in human cells. (2003) — 332 citations
• Quantification of protein half-lives in the budding yeast proteome (2006) — 722 citations
• A fast algorithm for joint reconstruction of ancestral amino acid sequences. (2000) — 355 citations
• Identification of functional modules using network topology and high-throughput data (2007) — 329 citations
• Discovering statistically significant biclusters in gene expression data (2002) — 979 citations
• Modelling and analysis of gene regulatory networks (2008) — 1,300 citations
• CLICK and EXPANDER: a system for clustering and visualizing gene expression data (2003) — 395 citations
• The De-Radicalization of Corporate Social Responsibility (2004) — 198 citations
• Cluster graph modification problems (2002) — 386 citations
• A comparative analysis of transcription factor binding models learned from PBM, HT-SELEX and ChIP data (2014) — 96 citations
• Dynamic Changes in the Copy Number of Pluripotency and Cell Proliferation Genes in Human ES and iPS Cells during Reprogramming and Time in Culture (2011) — 914 citations
• Center CLICK: A Clustering Algorithm with Applications to Gene Expression Analysis (2000) — 353 citations
• A clustering algorithm based on graph connectivity (2000) — 545 citations