Lukasz Kurgan

Molecular Biology · 2004–2021

A researcher in the Science corpus: 26 papers; trusts 167 researchers and is trusted by 43 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 563 citations into it; #869 of 17,773 by trust here, #2,390 by citations
• Materials Chemistry — 268 citations into it; #2,643 of 11,513 by trust here, #4,626 by citations
• Computational Biology & Bioinformatics — 76 citations into it
• Spectroscopy — 74 citations into it
• Cell Biology — 31 citations into it
• Computational Theory and Mathematics — 20 citations into it; #2,336 of 12,182 by trust here, #2,489 by citations
• Artificial Intelligence — 19 citations into it; #10,848 of 35,345 by trust here, #24,417 by citations
• Evaluation & Benchmarks — 19 citations into it

Whom Lukasz Kurgan trusts overall

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

1. Burkhard Rost
2. Zsuzsanna Dosztányi
3. Avner Schlessinger
4. Liam J. McGuffin
5. Vladimir N Uversky
6. A. Keith Dunker
7. Zhenling Peng
8. Usama M. Fayyad
9. David C. Jones
10. David T. Jones

Who trusts Lukasz Kurgan overall

1. Zhenling Peng
2. Fanchi Meng
3. Vladimir N Uversky
4. Bálint Mészáros
5. Jonathan J. Davis
6. Yu Yi
7. S. Kotsiantis
8. Jack Hanson
9. Zsuzsanna Dosztányi
10. Nataliya Sokolovska

Papers from Lukasz Kurgan's perspective

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

1. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.
2. Intrinsically unstructured proteins: re-assessing the protein structure-function paradigm.
3. Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features
4. Prediction and functional analysis of native disorder in proteins from the three kingdoms of life.
5. Intrinsically unstructured proteins. (TIBS -Trends in Biochemical Sciences. Regular ed)
6. SCOP: a structural classification of proteins database for the investigation of sequences and structures.
7. Intrinsic disorder and protein function. (Biochemistry)
8. Protein data bank
9. The importance of intrinsic disorder for protein phosphorylation. (Nucleic Acids Research)
10. Basic local alignment search tool.

Their papers

• SPINE X: Improving protein secondary structure prediction by multi-step learning coupled with prediction of solvent accessible surface area and backbone torsion angles (2011) — 258 citations
• Improved sequence-based prediction of disordered regions with multilayer fusion of multiple information sources (2010) — 176 citations
• MoRFpred, a computational tool for sequence-based prediction and characterization of short disorder-to-order transitioning binding regions in proteins (2012) — 340 citations
• DeepCNF-D: Predicting Protein Order/Disorder Regions by Weighted Deep Convolutional Neural Fields (2015) — 67 citations
• Molecular recognition features (MoRFs) in three domains of life. (2016) — 147 citations
• D2P2: database of disordered protein predictions (2012) — 668 citations
• Comprehensive comparative assessment of in-silico predictors of disordered regions. (2012) — 176 citations
• DFLpred: High-throughput prediction of disordered flexible linker regions in protein sequences (2016) — 77 citations
• High-throughput prediction of RNA, DNA and protein binding regions mediated by intrinsic disorder (2015) — 164 citations
• Exceptionally abundant exceptions: comprehensive characterization of intrinsic disorder in all domains of life (2014) — 345 citations
• Taxonomic Landscape of the Dark Proteomes: Whole‐Proteome Scale Interplay Between Structural Darkness, Intrinsic Disorder, and Crystallization Propensity (2018) — 35 citations
• iFC2: an integrated web-server for improved prediction of protein structural class, fold type, and secondary structure content (2010) — 12 citations
• Comprehensive review of methods for prediction of intrinsic disorder and its molecular functions (2017) — 161 citations
• Critical assessment of protein intrinsic disorder prediction (2020) — 286 citations
• Critical assessment of high-throughput standalone methods for secondary structure prediction (2011) — 54 citations
• Prediction of Disordered RNA, DNA, and Protein Binding Regions Using DisoRDPbind. (2017) — 76 citations
• Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1 (2021) — 3,841 citations
• A survey of Knowledge Discovery and Data Mining process models (2006) — 428 citations
• Genome‐scale prediction of proteins with long intrinsically disordered regions (2014) — 125 citations
• CAIM discretization algorithm (2004) — 460 citations