Oliver Kohlbacher

Molecular Biology · 1999–2021

A researcher in the Science corpus: 23 papers; trusts 29 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 301 citations into it; #3,413 of 17,773 by trust here, #1,785 by citations
• Computational Biology & Bioinformatics — 67 citations into it
• Spectroscopy — 65 citations into it
• Artificial Intelligence — 41 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Evaluation & Benchmarks — 14 citations into it
• Ecology — 9 citations into it
• Plant Science — 5 citations into it

Whom Oliver Kohlbacher trusts overall

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

1. Kuo-Chen Chou
2. Vladimir Naumovich Vapni
3. Robert C. Edgar
4. Rajesh Nair
5. Hongbin Shen
6. Chih-Jen Lin
7. Bernhard Schölkopf
8. Burkhard Rost
9. Terence P. Speed
10. Paul Horton

Who trusts Oliver Kohlbacher overall

1. Michael Heinzinger
2. Ahmed Elnaggar
3. Eric W. Deutsch
4. Tomás Pluskal
5. Marc Sturm
6. Sebastian Briesemeister
7. Yu Wang
8. Wouter M. Kouw

Papers from Oliver Kohlbacher's perspective

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

1. The Nature of Statistical Learning Theory
2. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.
3. LIBSVM: A library for support vector machines
4. Gene Ontology: tool for the unification of biology
5. Visualizing Data using t-SNE
6. Advances in kernel methods: support vector learning
7. The Pfam protein families database
8. Attention is All you Need (Neural Information Processing Systems)
9. Gradient-based learning applied to document recognition
10. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)

Their papers

• Sequence co-evolution gives 3D contacts and structures of protein complexes (2014) — 496 citations
• Large-scale discovery of protein interactions at residue resolution using co-evolution calculated from genomic sequences (2021) — 103 citations
• Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients (2018) — 792 citations
• OpenMS: a flexible open-source software platform for mass spectrometry data analysis (2016) — 599 citations
• MultiLoc2: integrating phylogeny and Gene Ontology terms improves subcellular protein localization prediction (2009) — 293 citations
• YLoc—an interpretable web server for predicting subcellular localization (2010) — 306 citations
• TOPP - the OpenMS proteomics pipeline (2007) — 299 citations
• Visualization of omics data for systems biology (2010) — 640 citations
• SherLoc2: a high-accuracy hybrid method for predicting subcellular localization of proteins. (2009) — 140 citations
• OptiType: precision HLA typing from next-generation sequencing data (2014) — 678 citations
• OpenMS – An open-source software framework for mass spectrometry (2008) — 646 citations
• Charting a dynamic DNA methylation landscape of the human genome (2013) — 1,316 citations
• NRPSpredictor2—a web server for predicting NRPS adenylation domain specificity (2011) — 588 citations
• Specificity prediction of adenylation domains in nonribosomal peptide synthetases (NRPS) using transductive support vector machines (TSVMs) (2005) — 429 citations
• Novel Machine Learning Methods for MHC Class I Binding Prediction (2010) — 39 citations
• 6th European Congress of Immunology, 1-4 September 2021, Virtual meeting. (2021) — 646 citations
• Proteome-scale discovery of protein interactions with residue-level resolution using sequence coevolution (2019) — 6 citations
• Food monitoring: Screening of the geographical origin of white asparagus using FT-NIR and machine learning (2019) — 75 citations
• Feature-Based Molecular Networking in the GNPS Analysis Environment (2019) — 1,337 citations
• From hype to reality: data science enabling personalized medicine (2018) — 359 citations