D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 46 Citations 8,208 160 World Ranking 1808 National Ranking 59
Biology and Biochemistry D-index 58 Citations 13,716 159 World Ranking 6116 National Ranking 464

Overview

What is he best known for?

The fields of study he is best known for:

  • Gene
  • DNA
  • Enzyme

The scientist’s investigation covers issues in Computational biology, Genetics, Proteomics, Software and Subcellular localization. His studies in Computational biology integrate themes in fields like Exome sequencing, Amino acid, Sequence analysis and DNA sequencing. Oliver Kohlbacher has researched Proteomics in several fields, including DNA microarray, Data mining, Bioinformatics and Mass spectrometry.

His Software study combines topics from a wide range of disciplines, such as Label free, File format, Quantitative proteomics and World Wide Web. His work deals with themes such as Protein subcellular localization prediction and Protein sequencing, which intersect with Subcellular localization. His Genomics study incorporates themes from Epitope, Epitope mapping, Precision medicine and Personalized medicine.

His most cited work include:

  • Charting a dynamic DNA methylation landscape of the human genome (891 citations)
  • Visualization of omics data for systems biology (501 citations)
  • OpenMS – An open-source software framework for mass spectrometry (500 citations)

What are the main themes of his work throughout his whole career to date?

Oliver Kohlbacher mostly deals with Computational biology, Bioinformatics, Data mining, Proteomics and Workflow. He has included themes like Genetics, Genome, Epitope, In silico and Major histocompatibility complex in his Computational biology study. His study in Proteomics is interdisciplinary in nature, drawing from both Proteome, Support vector machine and Mass spectrometry.

His Mass spectrometry research includes elements of Biological system and Metabolomics. Oliver Kohlbacher has included themes like Software, Cloud computing, Software engineering and Data science in his Workflow study. His Data science study integrates concerns from other disciplines, such as Visualization and Omics technologies.

He most often published in these fields:

  • Computational biology (21.05%)
  • Bioinformatics (14.62%)
  • Data mining (10.82%)

What were the highlights of his more recent work (between 2016-2021)?

  • Data science (10.82%)
  • Computational biology (21.05%)
  • Proteomics (12.28%)

In recent papers he was focusing on the following fields of study:

His primary areas of investigation include Data science, Computational biology, Proteomics, Human leukocyte antigen and Identification. His Data science research is multidisciplinary, incorporating perspectives in Data management, Elixir, Omics technologies, Workflow and Big data. In his research, Scalability, Data access, Data modeling, Metadata and Visualization is intimately related to Software, which falls under the overarching field of Workflow.

His biological study spans a wide range of topics, including Proteome, Genome and Exome. His Proteomics research includes elements of Chromatography, Metabolomics, Mass spectrometry and Inference. His Identification research incorporates elements of Software engineering and Shotgun proteomics.

Between 2016 and 2021, his most popular works were:

  • Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients. (233 citations)
  • Severe COVID-19 Is Marked by a Dysregulated Myeloid Cell Compartment. (226 citations)
  • From hype to reality: data science enabling personalized medicine (97 citations)

In his most recent research, the most cited papers focused on:

  • Gene
  • DNA
  • Enzyme

His main research concerns Human leukocyte antigen, Antigen, Immunotherapy, Immune system and Immunology. The concepts of his Human leukocyte antigen study are interwoven with issues in Proteome, Autoimmunity, Exome and Intracellular. His Antigen study incorporates themes from Cancer research and In silico.

The study incorporates disciplines such as Myeloid, Chronic lymphocytic leukemia, Pathogenesis and Respiratory failure in addition to Immune system. His work deals with themes such as Peripheral blood mononuclear cell, Gene signature, Myelopoiesis and Transplantation, which intersect with Immunology. His study looks at the relationship between Ovarian cancer and topics such as RNA-Seq, which overlap with Computational biology.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Charting a dynamic DNA methylation landscape of the human genome

Michael J. Ziller;Hongcang Gu;Fabian Müller;Julie Donaghey;Julie Donaghey.
Nature (2013)

1018 Citations

OpenMS – An open-source software framework for mass spectrometry

Marc Sturm;Andreas Bertsch;Clemens Gröpl;Andreas Hildebrandt.
BMC Bioinformatics (2008)

1003 Citations

Visualization of omics data for systems biology

Nils Gehlenborg;Seán I O'Donoghue;Nitin S Baliga;Alexander Goesmann.
Nature Methods (2010)

651 Citations

NRPSpredictor2-a web server for predicting NRPS adenylation domain specificity

Marc Röttig;Marnix H. Medema;Kai Blin;Tilmann Weber.
Nucleic Acids Research (2011)

544 Citations

Specificity prediction of adenylation domains in nonribosomal peptide synthetases (NRPS) using transductive support vector machines (TSVMs)

Christian Rausch;Tilmann Weber;Oliver Kohlbacher;Wolfgang Wohlleben.
Nucleic Acids Research (2005)

463 Citations

MultiLoc: prediction of protein subcellular localization using N-terminal targeting sequences, sequence motifs and amino acid composition

Annette Höglund;Pierre Dönnes;Torsten Blum;Hans-Werner Adolph.
Bioinformatics (2006)

406 Citations

Transcriptional and epigenetic dynamics during specification of human embryonic stem cells.

Casey A. Gifford;Michael Johannes Ziller;Michael Johannes Ziller;Hongcang Gu;Cole Trapnell;Cole Trapnell.
Cell (2013)

389 Citations

Sequence co-evolution gives 3D contacts and structures of protein complexes

Thomas A Hopf;Charlotta P I Schärfe;Charlotta P I Schärfe;João P G L M Rodrigues;Anna G Green.
eLife (2014)

369 Citations

OptiType: precision HLA typing from next-generation sequencing data.

András Szolek;Benjamin Schubert;Christopher Mohr;Marc Sturm.
Bioinformatics (2014)

339 Citations

TOPP---the OpenMS proteomics pipeline

Oliver Kohlbacher;Knut Reinert;Clemens Gröpl;Eva Lange.
Bioinformatics (2007)

326 Citations

Best Scientists Citing Oliver Kohlbacher

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Ruedi Aebersold

ETH Zurich

Publications: 113

Alexander Meissner

Alexander Meissner

Max Planck Institute for Molecular Genetics

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Pieter C. Dorrestein

Pieter C. Dorrestein

University of California, San Diego

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Albert Sickmann

Albert Sickmann

Leibniz Institute for Neurobiology

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Juan Antonio Vizcaíno

Juan Antonio Vizcaíno

European Bioinformatics Institute

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Henning Hermjakob

Henning Hermjakob

European Bioinformatics Institute

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Lennart Martens

Lennart Martens

Ghent University

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Debora S. Marks

Debora S. Marks

Harvard University

Publications: 41

Michael S. Kobor

Michael S. Kobor

University of British Columbia

Publications: 38

Eric W. Deutsch

Eric W. Deutsch

University of Washington

Publications: 37

René P. Zahedi

René P. Zahedi

McGill University

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Detlef Weigel

Detlef Weigel

Max Planck Institute for Developmental Biology

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Morten Nielsen

Morten Nielsen

Technical University of Denmark

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Stefan Stevanovic

Stefan Stevanovic

University of Tübingen

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Hans-Georg Rammensee

Hans-Georg Rammensee

University of Tübingen

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Korbinian Schneeberger

Korbinian Schneeberger

Max Planck Society

Publications: 31

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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