Sach Mukherjee

Molecular Biology · 2011–2021

A researcher in the Science corpus: 6 papers; trusts 29 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 81 citations into it; #3,835 of 17,773 by trust here, #9,727 by citations
• Artificial Intelligence — 48 citations into it
• Statistics and Probability — 35 citations into it
• Causal Inference & Discovery — 16 citations into it
• Oncology — 15 citations into it
• Probabilistic & Bayesian Methods — 13 citations into it
• Computational Theory and Mathematics — 12 citations into it
• Genetics — 8 citations into it

Whom Sach Mukherjee trusts overall

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

1. Darren J. Wilkinson
2. Tom Fawcett
3. Nir Friedman
4. Judea Pearl
5. B. Ellis
6. K. Burnham
7. Birgit Schoeberl
8. Daniel Marbach
9. Daniel Eaton
10. Boris N. Kholodenko

Who trusts Sach Mukherjee overall

1. Frederik Vissing Mikkelsen
2. N. Mangan
3. Thalia E. Chan
4. Chris J. Oates
5. Niels Richard Hansen

Papers from Sach Mukherjee's perspective

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

1. Causality : Models , Reasoning , and Inference
2. Bayesian Graphical Models for Discrete Data
3. High-dimensional graphs and variable selection with the Lasso
4. Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
5. Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks
6. How to infer gene networks from expression profiles (Molecular Systems Biology)
7. Stochastic Modelling for Systems Biology
8. Generating Realistic In Silico Gene Networks for Performance Assessment of Reverse Engineering Methods (J. Comput. Biol.)
9. Exact Bayesian structure learning from uncertain interventions
10. Causal inference in statistics: An overview

Their papers

• Inferring causal molecular networks: empirical assessment through a community-based effort (2016) — 222 citations
• Network Inference and Biological Dynamics (2011) — 81 citations
• Causal network inference using biochemical kinetics (2014) — 60 citations
• Joint estimation of multiple networks from time course data (2013) — 20 citations
• Network inference using steady-state data and Goldbeter-Koshland kinetics (2012) — 19 citations
• Swarm Learning for decentralized and confidential clinical machine learning (2021) — 792 citations