Jörg Gsponer
Molecular Biology · 2013–2020
A researcher in the Science corpus: 6 papers; trusts 32 researchers and is trusted by 16 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 93 citations into it; #2,430 of 17,773 by trust here, #7,980 by citations
- Materials Chemistry — 32 citations into it
- Computational Biology & Bioinformatics — 15 citations into it
- Genetics — 14 citations into it
- Spectroscopy — 13 citations into it
- Computational Theory and Mathematics — 7 citations into it
Whom Jörg Gsponer trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Zsuzsanna Dosztányi
- Chun Fang
- Bálint Mészáros
- David T. Jones
- Christopher J. Oldfield
- Eshel Faraggi
- István Simon
- Fatemeh Miri Disfani
- Nawar Malhis
- Amrita Mohan
Who trusts Jörg Gsponer overall
- Fanchi Meng
- Bálint Mészáros
- Nawar Malhis
- Lukasz Kurgan
- Vladimir N Uversky
- Zhenling Peng
- Márton Miskei
- Gábor Erdös
Papers from Jörg Gsponer's perspective
Ordered by how strongly the researchers Jörg Gsponer trusts endorse each paper. Same corpus, a different order for every researcher.
- Prediction and functional analysis of native disorder in proteins from the three kingdoms of life.
- Intrinsically unstructured proteins. (TIBS -Trends in Biochemical Sciences. Regular ed)
- Intrinsically disordered protein.
- Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.
- Intrinsically Disordered Proteins in Cellular Signaling and Regulation
- Characterization of molecular recognition features, MoRFs, and their binding partners.
- Prediction of Protein Binding Regions in Disordered Proteins
- Intrinsically unstructured proteins: re-assessing the protein structure-function paradigm.
- Protein data bank
- MoRFpred, a computational tool for sequence-based prediction and characterization of short disorder-to-order transitioning binding regions in proteins
Their papers
- Computational identification of MoRFs in protein sequences (2015) — 78 citations
- Computational Identification of MoRFs in Protein Sequences Using Hierarchical Application of Bayes Rule (2015) — 52 citations
- MoRFchibi SYSTEM: software tools for the identification of MoRFs in protein sequences (2016) — 147 citations
- What’s in a name? Why these proteins are intrinsically disordered (2013) — 264 citations
- Critical assessment of protein intrinsic disorder prediction (2020) — 286 citations
- LIST-S2: taxonomy based sorting of deleterious missense mutations across species (2020) — 90 citations