Bjoern Peters

Molecular Biology · 2005–2021

A researcher in the Science corpus: 29 papers; trusts 24 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 164 citations into it; #1,603 of 17,773 by trust here, #1,764 by citations
• Immunology — 100 citations into it; #413 of 2,160 by trust here, #624 by citations
• Radiology, Nuclear Medicine and Imaging — 44 citations into it; #1,563 of 3,265 by trust here, #679 by citations
• Genetics — 25 citations into it
• Microbiology — 7 citations into it; #40 of 213 by trust here, #72 by citations
• Computational Theory and Mathematics — 6 citations into it

Whom Bjoern Peters trusts overall

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

1. Morten Nielsen
2. Claus Lundegaard
3. Leo Breiman
4. Massimo Andreatta
5. Ole Lund
6. John Sidney
7. Pedro A. Reche
8. Jens Vindahl Kringelum
9. Peng Wang

Who trusts Bjoern Peters overall

1. Morten Nielsen
2. Peng Wang
3. John Sidney
4. Massimo Andreatta
5. Shutao Mei
6. Alessandro Sette
7. Claus Lundegaard
8. Ward Fleri
9. Alba Grifoni
10. Yohan Kim

Papers from Bjoern Peters's perspective

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

1. A Community Resource Benchmarking Predictions of Peptide Binding to MHC-I Molecules (PLoS Comput. Biol.)
2. NetMHCpan, a Method for Quantitative Predictions of Peptide Binding to Any HLA-A and -B Locus Protein of Known Sequence
3. Prediction of MHC class I binding peptides using profile motifs. (Human Immunology)
4. Reliable prediction of T‐cell epitopes using neural networks with novel sequence representations
5. The Protein Data Bank
6. The Immune Epitope Database and Analysis Resource: From Vision to Blueprint (PLoS Biology)
7. The immune epitope database (IEDB) 3.0 (Nucleic Acids Res.)
8. ElliPro: a new structure-based tool for the prediction of antibody epitopes (BMC Bioinformatics)
9. Immune epitope database analysis resource (IEDB-AR) (Nucleic Acids Res.)
10. An integrative approach to CTL epitope prediction: A combined algorithm integrating MHC class I binding, TAP transport efficiency, and proteasomal cleavage predictions (European Journal of Immunology)

Their papers

• A Community Resource Benchmarking Predictions of Peptide Binding to MHC-I Molecules (2006) — 308 citations
• The Immune Epitope Database (IEDB): 2018 update (2018) — 1,975 citations
• BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes (2017) — 1,496 citations
• The immune epitope database (IEDB) 3.0 (2014) — 1,073 citations
• The Immune Epitope Database and Analysis Resource: From Vision to Blueprint (2005) — 309 citations
• NetMHCpan, a Method for Quantitative Predictions of Peptide Binding to Any HLA-A and -B Locus Protein of Known Sequence (2007) — 693 citations
• Improved methods for predicting peptide binding affinity to MHC class II molecules (2018) — 725 citations
• Generating quantitative models describing the sequence specificity of biological processes with the stabilized matrix method (2005) — 562 citations
• NetMHCpan 4.0: Improved peptide-MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data (2017) — 1,083 citations
• The Immune Epitope Database 2.0 (2009) — 672 citations
• Immune epitope database analysis resource (IEDB-AR) (2008) — 391 citations
• Peptide binding predictions for HLA DR, DP and DQ molecules (2010) — 677 citations
• A Systematic Assessment of MHC Class II Peptide Binding Predictions and Evaluation of a Consensus Approach (2008) — 853 citations
• Immune epitope database analysis resource (2012) — 514 citations
• Properties of MHC Class I Presented Peptides That Enhance Immunogenicity (2013) — 836 citations
• The Ontology for Biomedical Investigations (2016) — 373 citations
• Impact of genetic polymorphisms on human immune cell gene expression (2018) — 741 citations
• Targets of T Cell Responses to SARS-CoV-2 Coronavirus in Humans with COVID-19 Disease and Unexposed Individuals (2020) — 3,322 citations
• NetMHCpan-4.1 and NetMHCIIpan-4.0: improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand data (2020) — 1,960 citations
• A Sequence Homology and Bioinformatic Approach Can Predict Candidate Targets for Immune Responses to SARS-CoV-2 (2020) — 923 citations