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 54 Citations 11,587 185 World Ranking 1095 National Ranking 11

Overview

What is he best known for?

The fields of study he is best known for:

  • Gene
  • Enzyme
  • Operating system

Lennart Martens spends much of his time researching Proteomics, Proteome, Bioinformatics, Biochemistry and Computational biology. His Proteomics research focuses on Proteomics Standards Initiative in particular. The various areas that Lennart Martens examines in his Proteome study include Platelet, Integrin, Quantitative analysis, Mass spectrometry and Protein identification.

The concepts of his Bioinformatics study are interwoven with issues in Proteomics methods, Data science and Library science. His work investigates the relationship between Data science and topics such as Human proteome project that intersect with problems in Standardization. His Biochemistry study combines topics in areas such as Immunology and Pathogenesis.

His most cited work include:

  • ProteomeXchange provides globally coordinated proteomics data submission and dissemination (1926 citations)
  • The minimum information about a proteomics experiment (MIAPE) (608 citations)
  • The minimum information about a proteomics experiment (MIAPE) (608 citations)

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

His main research concerns Proteomics, Computational biology, Data science, Proteome and Bioinformatics. His Proteomics research includes themes of Data mining, Identification, Peptide and Mass spectrometry. His Identification study combines topics from a wide range of disciplines, such as Software and World Wide Web, Search engine.

Lennart Martens frequently studies issues relating to Metaproteomics and Computational biology. Lennart Martens has researched Data science in several fields, including Standardization and Field. His Proteome research is multidisciplinary, relying on both Protein identification, Shotgun proteomics and Human proteome project.

He most often published in these fields:

  • Proteomics (34.12%)
  • Computational biology (19.29%)
  • Data science (17.80%)

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

  • Metaproteomics (6.23%)
  • Workflow (8.31%)
  • Proteomics (34.12%)

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

His scientific interests lie mostly in Metaproteomics, Workflow, Proteomics, Proteogenomics and Computational biology. His studies deal with areas such as Web application, Set and Semantic similarity as well as Metaproteomics. His work in Workflow addresses subjects such as Machine learning, which are connected to disciplines such as Graphical user interface, Python and Atomic composition.

His work deals with themes such as Variant Call Format and Mass spectrometry, which intersect with Proteomics. The Proteogenomics study combines topics in areas such as Label-free quantification, Software, Artificial intelligence and Identification. Lennart Martens has included themes like Identifier, Proteome and Shotgun proteomics in his Computational biology study.

Between 2019 and 2021, his most popular works were:

  • Anatomy and evolution of database search engines-a central component of mass spectrometry based proteomic workflows. (38 citations)
  • Removing the Hidden Data Dependency of DIA with Predicted Spectral Libraries. (12 citations)
  • The Age of Data-Driven Proteomics: How Machine Learning Enables Novel Workflows. (10 citations)

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

  • Gene
  • Enzyme
  • Artificial intelligence

The scientist’s investigation covers issues in Workflow, Metaproteomics, Chromatography, Retention time and Field. His Workflow research incorporates themes from Identification, Machine learning, Deep learning, Artificial intelligence and Ambiguity. Lennart Martens interconnects Shotgun proteomics, Database search engine, Search engine and Component in the investigation of issues within Identification.

His Metaproteomics research incorporates elements of Pipeline, Web application, World Wide Web, Interface and InterPro. His study in Retention time is interdisciplinary in nature, drawing from both Python, Graphical user interface, Atomic composition and Peptide. His work carried out in the field of Field brings together such families of science as End-to-end principle, Functional annotation, Data processing and Data science.

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

ProteomeXchange provides globally coordinated proteomics data submission and dissemination

Juan A. Vizcaíno;Eric W Deutsch;Rui Wang;Attila Csordas.
Nature Biotechnology (2014)

2213 Citations

The minimum information about a proteomics experiment (MIAPE)

Chris F. Taylor;Chris F. Taylor;Norman W. Paton;Norman W. Paton;Kathryn S. Lilley;Kathryn S. Lilley;Pierre Alain Binz;Pierre Alain Binz.
Nature Biotechnology (2007)

728 Citations

Exploring proteomes and analyzing protein processing by mass spectrometric identification of sorted N-terminal peptides.

Kris Gevaert;Marc Goethals;Lennart Martens;Jozef Van Damme.
Nature Biotechnology (2003)

625 Citations

The first comprehensive and quantitative analysis of human platelet protein composition allows the comparative analysis of structural and functional pathways.

Julia M. Burkhart;Marc Vaudel;Stepan Gambaryan;Sonja Radau.
Blood (2012)

561 Citations

Improved visualization of protein consensus sequences by iceLogo.

Niklaas Colaert;Niklaas Colaert;Kenny Helsens;Kenny Helsens;Lennart Martens;Joël Vandekerckhove;Joël Vandekerckhove.
Nature Methods (2009)

554 Citations

PRIDE: The proteomics identifications database

Lennart Martens;Henning Hermjakob;Philip Jones;Marcin Adamski.
Proteomics (2005)

536 Citations

mzML - a Community Standard for Mass Spectrometry Data

Lennart Martens;Matthew Chambers;Marc Sturm;Darren Kessner.
Molecular & Cellular Proteomics (2011)

517 Citations

LNCipedia: a database for annotated human lncRNA transcript sequences and structures.

Pieter-Jan Volders;Kenny Helsens;Xiaowei Wang;Björn Menten.
Nucleic Acids Research (2013)

495 Citations

PeptideShaker enables reanalysis of MS-derived proteomics data sets

Marc Vaudel;Marc Vaudel;Julia M Burkhart;René P Zahedi;Eystein Oveland.
Nature Biotechnology (2015)

388 Citations

A HUPO test sample study reveals common problems in mass spectrometry–based proteomics

Alexander W. Bell;Eric W. Deutsch;Catherine E. Au;Robert E. Kearney.
Nature Methods (2009)

344 Citations

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Best Scientists Citing Lennart Martens

Kris Gevaert

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Ruedi Aebersold

Ruedi Aebersold

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Henning Hermjakob

Henning Hermjakob

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Albert Sickmann

Albert Sickmann

Leibniz Institute for Neurobiology

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Eric W. Deutsch

Eric W. Deutsch

University of Washington

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Christopher M. Overall

Christopher M. Overall

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Petra Van Damme

Petra Van Damme

Ghent University

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Juan Antonio Vizcaíno

Juan Antonio Vizcaíno

European Bioinformatics Institute

Publications: 69

Juri Rappsilber

Juri Rappsilber

University of Edinburgh

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Matthias Mann

Matthias Mann

Max Planck Institute of Biochemistry

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Albert J. R. Heck

Albert J. R. Heck

Utrecht University

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René P. Zahedi

René P. Zahedi

McGill University

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Gilbert S. Omenn

Gilbert S. Omenn

University of Michigan–Ann Arbor

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Robert L. Moritz

Robert L. Moritz

Institute for Systems Biology

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Joël Vandekerckhove

Joël Vandekerckhove

Ghent University

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Akhilesh Pandey

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