Jesse D. Bloom
Infectious Diseases · 2004–2021
A researcher in the Science corpus: 20 papers; trusts 60 researchers and is trusted by 26 researchers here, as inferred from the citation graph.
Subfields
- Infectious Diseases — 204 citations into it
- Molecular Biology — 172 citations into it; #1,477 of 17,773 by trust here, #1,704 by citations
- Genetics — 74 citations into it; #1,919 of 6,854 by trust here, #1,251 by citations
- Epidemiology — 73 citations into it; #276 of 2,148 by trust here, #558 by citations
- Materials Chemistry — 29 citations into it
- Computational Biology & Bioinformatics — 26 citations into it
- Cardiology and Cardiovascular Medicine — 11 citations into it
- Artificial Intelligence — 10 citations into it
Whom Jesse D. Bloom trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Joseph Felsenstein
- John P. Huelsenbeck
- Fredrik Ronquist
- Robert C. Edgar
- E. Hoffmann
- J. Kyte
- Hongyi Zhou
- L. Gong
- Ziheng Yang
- M. Michael Gromiha
Who trusts Jesse D. Bloom overall
- Tyler N. Starr
- Julian Echave
- Benjamin T. Porebski
- L. Gong
- Michael B. Doud
- Philip A. Romero
- Sergey Kryazhimskiy
- Eleisha L. Jackson
- Nicholas C. Wu
- Andreas Wagner
Papers from Jesse D. Bloom's perspective
Ordered by how strongly the researchers Jesse D. Bloom trusts endorse each paper. Same corpus, a different order for every researcher.
- Predicting changes in the stability of proteins and protein complexes: a study of more than 1000 mutations.
- Evolutionary trees from DNA sequences: A maximum likelihood approach (Journal of Molecular Evolution)
- MUSCLE: multiple sequence alignment with high accuracy and high throughput.
- The rapid generation of mutation data matrices from protein sequences
- A general empirical model of protein evolution derived from multiple protein families using a maximum-likelihood approach.
- MrBayes 3: Bayesian phylogenetic inference under mixed models (Bioinform.)
- MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability
- Codon-substitution models for heterogeneous selection pressure at amino acid sites. (Genetics)
- Protein stability promotes evolvability.
- A DNA transfection system for generation of influenza A virus from eight plasmids. (Proceedings of the National Academy of Sciences of the United States of America)
Their papers
- Protein stability promotes evolvability. (2006) — 1,153 citations
- Permissive Secondary Mutations Enable the Evolution of Influenza Oseltamivir Resistance (2010) — 678 citations
- Mutational effects on stability are largely conserved during protein evolution (2013) — 134 citations
- Inferring Stabilizing Mutations from Protein Phylogenies: Application to Influenza Hemagglutinin (2009) — 63 citations
- Thermodynamic prediction of protein neutrality. (2004) — 215 citations
- Stability-mediated epistasis constrains the evolution of an influenza protein (2013) — 336 citations
- Comprehensive mapping of mutations to the SARS-CoV-2 receptor-binding domain that affect recognition by polyclonal human serum antibodies (2021) — 749 citations
- Deep mutational scanning of SARS-CoV-2 receptor binding domain reveals constraints on folding and ACE2 binding (2020) — 1,185 citations
- Why highly expressed proteins evolve slowly. (2005) — 805 citations
- Complete mapping of mutations to the SARS-CoV-2 spike receptor-binding domain that escape antibody recognition (2020) — 934 citations
- The inherent mutational tolerance and antigenic evolvability of influenza hemagglutinin (2014) — 203 citations
- Deep Mutational Scanning of SARS-CoV-2 Receptor Binding Domain Reveals Constraints on Folding and ACE2 Binding (2020) — 968 citations
- Mapping person-to-person variation in viral mutations that escape polyclonal serum targeting influenza hemagglutinin (2019) — 97 citations
- Author response: Mapping person-to-person variation in viral mutations that escape polyclonal serum targeting influenza hemagglutinin (2019) — 5 citations
- Prospective mapping of viral mutations that escape antibodies used to treat COVID-19 (2020) — 627 citations
- Computational design of trimeric influenza neutralizing proteins targeting the hemagglutinin receptor binding site (2017) — 122 citations
- A human coronavirus evolves antigenically to escape antibody immunity (2020) — 216 citations
- Protocol and Reagents for Pseudotyping Lentiviral Particles with SARS-CoV-2 Spike Protein for Neutralization Assays (2020) — 780 citations
- Sera from Individuals with Narrowly Focused Influenza Virus Antibodies Rapidly Select Viral Escape Mutations In Ovo (2018) — 16 citations
- Accurate Measurement of the Effects of All Amino-Acid Mutations on Influenza Hemagglutinin (2016) — 220 citations