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 31 Citations 3,780 116 World Ranking 5287 National Ranking 191

Overview

What is he best known for?

The fields of study he is best known for:

  • Gene
  • DNA
  • Genetics

His primary scientific interests are in Data mining, Cluster analysis, Software, Biological data and Gene. His work on Visualization as part of general Data mining research is often related to Quantification methods, thus linking different fields of science. The study incorporates disciplines such as Text mining, Heuristic and Transitive relation in addition to Cluster analysis.

He has researched Software in several fields, including Bioinformatics, Ensemble learning, Pre-MicroRNA, Algorithm and Data set. His work in Bioinformatics tackles topics such as Workflow which are related to areas like Computational biology. His work on Systems biology as part of general Computational biology research is frequently linked to Relational database management system, thereby connecting diverse disciplines of science.

His most cited work include:

  • clusterMaker: a multi-algorithm clustering plugin for Cytoscape (323 citations)
  • AltAnalyze and DomainGraph: analyzing and visualizing exon expression data (209 citations)
  • Graph-based analysis and visualization of experimental results with ONDEX (175 citations)

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

Computational biology, Gene, Data mining, Systems biology and Genetics are his primary areas of study. His Computational biology study combines topics from a wide range of disciplines, such as Genome, Interactome and Gene regulatory network. His research in Data mining intersects with topics in Software, Set and Cluster analysis.

His study in Software is interdisciplinary in nature, drawing from both Information retrieval and Bioinformatics. His work deals with themes such as Data type and Biological data, which intersect with Cluster analysis. His studies in Systems biology integrate themes in fields like DNA microarray, Biological network, Data science and Protein–protein interaction.

He most often published in these fields:

  • Computational biology (43.01%)
  • Gene (19.35%)
  • Data mining (16.13%)

What were the highlights of his more recent work (between 2019-2021)?

  • Computational biology (43.01%)
  • Systems medicine (12.54%)
  • Network medicine (6.45%)

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

Jan Baumbach mainly focuses on Computational biology, Systems medicine, Network medicine, Gene and Systems biology. His Computational biology research incorporates themes from Infectious disease, Exon, Interactome, Coronavirus and Gene regulatory network. His Exon research includes elements of Binding site and Protein–protein interaction.

His research integrates issues of Drug repositioning, Disease, Neuroscience, Data science and Big data in his study of Systems medicine. His biological study spans a wide range of topics, including Human interactome, KEGG, Signalling and WikiPathways : Pathways for the people. His Gene research is multidisciplinary, incorporating elements of Ensemble learning and Omics.

Between 2019 and 2021, his most popular works were:

  • Mass-spectrometry-based draft of the Arabidopsis proteome. (86 citations)
  • Exploring the SARS-CoV-2 virus-host-drug interactome for drug repurposing. (48 citations)
  • Exploring the SARS-CoV-2 virus-host-drug interactome for drug repurposing. (48 citations)

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

  • Gene
  • DNA
  • Statistics

Computational biology, Network medicine, Systems medicine, Coronavirus and Interactome are his primary areas of study. He combines subjects such as RNA, RNA-binding protein, RNA splicing, Exon and Gene regulatory network with his study of Computational biology. The concepts of his Gene regulatory network study are interwoven with issues in Bioinformatics, Organism, Transcriptional regulation, Adaptation and Regulation of gene expression.

His study in Network medicine is interdisciplinary in nature, drawing from both Key, Analytics and Knowledge management. His Systems medicine study is focused on Systems biology in general. Jan Baumbach interconnects Precision medicine, Position paper, Drug repositioning, Viral life cycle and Interoperability in the investigation of issues within Systems 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

clusterMaker: a multi-algorithm clustering plugin for Cytoscape

John H Morris;Leonard Apeltsin;Aaron M Newman;Jan Baumbach.
BMC Bioinformatics (2011)

393 Citations

AltAnalyze and DomainGraph: analyzing and visualizing exon expression data

Dorothea Emig;Nathan Salomonis;Jan Baumbach;Thomas Lengauer.
Nucleic Acids Research (2010)

266 Citations

Graph-based analysis and visualization of experimental results with ONDEX

Jacob Köhler;Jan Baumbach;Jan Taubert;Michael Specht.
Bioinformatics (2006)

240 Citations

Comparing the performance of biomedical clustering methods

Christian Wiwie;Jan Baumbach;Richard Röttger.
Nature Methods (2015)

185 Citations

Current breathomics--a review on data pre-processing techniques and machine learning in metabolomics breath analysis.

A Smolinska;A-Ch Hauschild;R R R Fijten;J W Dallinga.
Journal of Breath Research (2014)

133 Citations

Partitioning biological data with transitivity clustering.

Tobias Wittkop;Tobias Wittkop;Tobias Wittkop;Dorothea Emig;Sita J. Lange;Sven Rahmann.
Nature Methods (2010)

128 Citations

Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology

Gregor Sturm;Francesca Finotello;Florent Petitprez;Jitao David Zhang.
Bioinformatics (2019)

118 Citations

The GlxR regulon of the amino acid producer Corynebacterium glutamicum: in silico and in vitro detection of DNA binding sites of a global transcription regulator.

Thomas A. Kohl;Jan Baumbach;Britta Jungwirth;Alfred Pühler.
Journal of Biotechnology (2008)

102 Citations

Evidence for reductive genome evolution and lateral acquisition of virulence functions in two Corynebacterium pseudotuberculosis strains.

Jerônimo C. Ruiz;Vívian D'Afonseca;Artur Silva;Amjad Ali.
PLOS ONE (2011)

101 Citations

Large scale clustering of protein sequences with FORCE -A layout based heuristic for weighted cluster editing

Tobias Wittkop;Jan Baumbach;Francisco P Lobo;Francisco P Lobo;Sven Rahmann.
BMC Bioinformatics (2007)

93 Citations

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Mitsubishi Group (Japan)

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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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