Charlotte M. Deane
Molecular Biology · 1998–2023
A researcher in the Science corpus: 17 papers; trusts 29 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 164 citations into it; #3,488 of 17,773 by trust here, #8,381 by citations
- Computational Theory and Mathematics — 79 citations into it; #8,975 of 12,182 by trust here, #5,465 by citations
- Materials Chemistry — 50 citations into it
- Computational Biology & Bioinformatics — 43 citations into it
- Computational Chemistry & Drug Discovery — 37 citations into it
- Radiology, Nuclear Medicine and Imaging — 33 citations into it; #710 of 3,265 by trust here, #1,741 by citations
- Immunology — 21 citations into it; #501 of 2,160 by trust here, #1,965 by citations
- Spectroscopy — 18 citations into it
Whom Charlotte M. Deane trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Robert C. Edgar
- James Dunbar
- Alexey G. Murzin
- Weizhong Li
- Andrej Sali
- Liisa Holm
- Roger A. Sayle
- S. Parasuraman
- Tom L. Blundell
- Yang Zhang
Who trusts Charlotte M. Deane overall
- Erik S. Wright
- Ragul Gowthaman
- James Dunbar
- Matthew I. J. Raybould
- Tobias Hegelund Olsen
- Sitao Wu
- Yue Lu
- Victor A. Simossis
- Julia Koehler Leman
- Brian G. Pierce
Papers from Charlotte M. Deane's perspective
Ordered by how strongly the researchers Charlotte M. Deane trusts endorse each paper. Same corpus, a different order for every researcher.
- The Protein Data Bank.
- Protein Structure Prediction and Structural Genomics
- MUSCLE: multiple sequence alignment with high accuracy and high throughput.
- SCOP: a structural classification of proteins database for the investigation of sequences and structures.
- Visualizing Data using t-SNE
- Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences
- The Protein Data Bank
- TM-align: a protein structure alignment algorithm based on the TM-score
- FUGUE: sequence-structure homology recognition using environment-specific substitution tables and structure-dependent gap penalties. (Journal of Molecular Biology)
- Semi-Supervised Classification with Graph Convolutional Networks (International Conference on Learning Representations)
Their papers
- MEDELLER: homology-based coordinate generation for membrane proteins (2010) — 100 citations
- PoseBusters: AI-based docking methods fail to generate physically valid poses or generalise to novel sequences (2023) — 343 citations
- Antibody i-Patch prediction of the antibody binding site improves rigid local antibody-antigen docking. (2013) — 91 citations
- Deep generative design with 3D pharmacophoric constraints (2021) — 85 citations
- SAbPred: a structure-based antibody prediction server (2016) — 197 citations
- CoV-AbDab: the Coronavirus Antibody Database (2020) — 349 citations
- ANARCI: antigen receptor numbering and receptor classification (2015) — 409 citations
- Five computational developability guidelines for therapeutic antibody profiling (2019) — 334 citations
- Observed Antibody Space: A diverse database of cleaned, annotated, and translated unpaired and paired antibody sequences (2021) — 343 citations
- Fragment Merging Using a Graph Database Samples Different Catalogue Space than Similarity Search (2023) — 21 citations
- The use of a graph database is a complementary approach to a classical similarity search for identifying commercially available fragment merges (2022)
- Protein-Ligand Interaction Graphs: Learning from Ligand-Shaped 3D Interaction Graphs to Improve Binding Affinity Prediction (2022) — 24 citations
- Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction (2017) — 53 citations
- Memoir: template-based structure prediction for membrane proteins (2013) — 41 citations
- SAbDab: the structural antibody database (2013) — 704 citations
- HOMSTRAD: A database of protein structure alignments for homologous families (1998)
- distance correlation