Assaf Gottlieb
Molecular Biology · 2006–2011
A researcher in the Science corpus: 3 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 48 citations into it
- Pharmacology — 10 citations into it
- Genetics — 7 citations into it
Whom Assaf Gottlieb trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Shufeng Zhou
- Minoru Kanehisa
- Peter N. Robinson
- Roded Sharan
- Michael Kuhn
- Nicholas P. Tatonetti
- David S. Wishart
- Susumu Goto
- Stefan Mundlos
- Isabelle M Guyon
Who trusts Assaf Gottlieb overall
- Ping Zhang
- Feixiong Cheng
- Michael Kuhn
- Yujie You
- Fei Wang
- Daniel S. Himmelstein
- Xiang Yue
- Zhongming Zhao
- Yuhao Wang
- Marinka Zitnik
Papers from Assaf Gottlieb's perspective
Ordered by how strongly the researchers Assaf Gottlieb trusts endorse each paper. Same corpus, a different order for every researcher.
- DrugBank: a knowledgebase for drugs, drug actions and drug targets
- KEGG: Kyoto Encyclopedia of Genes and Genomes (Nucleic Acids Res.)
- Predicting new molecular targets for known drugs
- Drugs behave as substrates, inhibitors and inducers of human cytochrome P450 3A4. (Current drug metabolism)
- Coupled two-way clustering analysis of gene microarray data. (Proceedings of the National Academy of Sciences of the United States of America)
- Data-Driven Prediction of Drug Effects and Interactions
- An Introduction to Variable and Feature Selection
- Singular value decomposition for genome-wide expression data processing and modeling. (Proceedings of the National Academy of Sciences of the United States of America)
- The information bottleneck method
- 'Gene shaving' as a method for identifying distinct sets of genes with similar expression patterns (Genome Biology)
Their papers
- PREDICT: a method for inferring novel drug indications with application to personalized medicine (2011) — 815 citations
- Novel Unsupervised Feature Filtering of Biological Data (2006) — 321 citations
- Molecular Systems Biology Peer Review Process File Indi: a Computational Framework for Inferring Drug Interactions and Their Associated Recommendations Transaction Report