Massimo Andreatta

Molecular Biology · 2011–2021

A researcher in the Science corpus: 7 papers; trusts 11 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 65 citations into it; #3,193 of 17,773 by trust here, #6,283 by citations
• Immunology — 29 citations into it; #292 of 2,160 by trust here, #1,367 by citations
• Radiology, Nuclear Medicine and Imaging — 17 citations into it; #946 of 3,265 by trust here, #1,299 by citations
• Microbiology — 8 citations into it

Whom Massimo Andreatta trusts overall

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

1. Morten Nielsen
2. Ole Lund
3. Claus Lundegaard
4. Steven Henikoff
5. Bjoern Peters
6. Simon Mason
7. Jorja G. Henikoff
8. N. Graham
9. Alessandro Sette
10. Kasper Lamberth

Who trusts Massimo Andreatta overall

1. Yeeleng Scott Vang
2. Morten Nielsen
3. Vanessa Isabell Jurtz
4. Sinu Paul
5. Xiaohui S. Xie
6. Ward Fleri
7. Bjoern Peters
8. Paolo Marcatili

Papers from Massimo Andreatta's perspective

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

1. Prediction of MHC class I binding peptides using profile motifs. (Human Immunology)
2. Amino acid substitution matrices from protein blocks.
3. Reliable prediction of T‐cell epitopes using neural networks with novel sequence representations
4. A Community Resource Benchmarking Predictions of Peptide Binding to MHC-I Molecules (PLoS Comput. Biol.)
5. NetMHCpan, a Method for Quantitative Predictions of Peptide Binding to Any HLA-A and -B Locus Protein of Known Sequence
6. The immune epitope database (IEDB) 3.0 (Nucleic Acids Res.)
7. ElliPro: a new structure-based tool for the prediction of antibody epitopes (BMC Bioinformatics)
8. Improved method for predicting linear B-cell epitopes (Immunome Research)
9. NetMHCpan, a method for MHC class I binding prediction beyond humans
10. ProPred: prediction of HLA-DR binding sites (Bioinform.)

Their papers

• Improved methods for predicting peptide binding affinity to MHC class II molecules (2018) — 725 citations
• NetMHCpan 4.0: Improved peptide-MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data (2017) — 1,083 citations
• Gapped sequence alignment using artificial neural networks: application to the MHC class I system (2016) — 1,025 citations
• Using Electronic Patient Records to Discover Disease Correlations and Stratify Patient Cohorts (2011) — 309 citations
• NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length datasets (2016) — 482 citations
• IEDB-AR: immune epitope database—analysis resource in 2019 (2019) — 357 citations
• UCell: Robust and scalable single-cell gene signature scoring (2021) — 841 citations