What is he best known for?
The fields of study he is best known for:
- Gene
- DNA
- Programming language
His primary areas of investigation include Resource, Computational biology, Nicotinic agonist, Bioinformatics and Receptor.
His Computational biology research incorporates themes from Data type, Metabolomics and Representation.
The concepts of his Nicotinic agonist study are interwoven with issues in Biophysics, Protein subunit, Neuroscience and Acetylcholine receptor.
The Bioinformatics study combines topics in areas such as Levodopa, Disease, Parkinson's disease and Neurotrophic factors.
Nicolas Le Novère interconnects Signalling and Cell biology in the investigation of issues within Receptor.
His BioModels Database study is related to the wider topic of SBML.
His most cited work include:
- A community-driven global reconstruction of human metabolism (764 citations)
- A community-driven global reconstruction of human metabolism (764 citations)
- Nicotinic receptors at the amino acid level. (696 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Systems biology, SBML, Software, Data science and Markup language.
Systems biology is a subfield of Computational biology that Nicolas Le Novère explores.
His SBML research is multidisciplinary, incorporating elements of Programming language, Theoretical computer science and Computational model.
His Software research integrates issues from The Internet, World Wide Web and Data mining.
His Markup language study integrates concerns from other disciplines, such as Biological network and Modelling biological systems.
His BioModels Database study combines topics in areas such as Information retrieval and Bioinformatics.
He most often published in these fields:
- Systems biology (31.16%)
- SBML (24.19%)
- Software (18.60%)
What were the highlights of his more recent work (between 2016-2021)?
- Data science (12.56%)
- Cell biology (11.16%)
- Systems biology (31.16%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Data science, Cell biology, Systems biology, Software and Synthetic biology.
His Data science study integrates concerns from other disciplines, such as Domain, Variety and Interoperability.
Nicolas Le Novère has included themes like Real time Java, Java annotation, Java and Integrative bioinformatics in his Systems biology study.
His Software study combines topics from a wide range of disciplines, such as Python, Software engineering, Robustness and Source code.
In his research, Programming language is intimately related to SBML, which falls under the overarching field of The Internet.
His study explores the link between Data exchange and topics such as Visualization that cross with problems in Computational biology.
Between 2016 and 2021, his most popular works were:
- The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core. (121 citations)
- PTEN Regulates PI(3,4)P2 Signaling Downstream of Class I PI3K (91 citations)
- Identifiers for the 21st century : How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data (56 citations)
In his most recent research, the most cited papers focused on:
Nicolas Le Novère focuses on Data science, Best practice, Reuse, The Internet and Software.
The Data science study combines topics in areas such as ENCODE, Translational medicine and Systems biomedicine.
His The Internet research integrates issues from Identifier and Data integration.
His Software research focuses on subjects like Measure, which are linked to Systems biology.
His Systems biology study frequently draws connections between adjacent fields such as Set.
In his study, which falls under the umbrella issue of SBML, Programming language is strongly linked to MathML.
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