What is he best known for?
The fields of study he is best known for:
Steven E. Brenner mainly investigates Genetics, Computational biology, Bioinformatics, Structural Classification of Proteins database and Gene.
The RNA splicing, Genome, Human genome and Sequence analysis research Steven E. Brenner does as part of his general Genetics study is frequently linked to other disciplines of science, such as Chain termination, therefore creating a link between diverse domains of science.
His Computational biology research incorporates themes from Metagenomics, Annotation, Sequence alignment and Genomics.
His Bioinformatics research includes elements of Sequence logo, Set, Structural genomics and Source code.
His Structural Classification of Proteins database research is multidisciplinary, incorporating elements of Information retrieval, Database and Pairwise comparison.
In his work, Sequence is strongly intertwined with Similarity, which is a subfield of Pairwise comparison.
His most cited work include:
- WebLogo: A Sequence Logo Generator (7973 citations)
- WebLogo: A Sequence Logo Generator (7973 citations)
- SCOP: a structural classification of proteins database for the investigation of sequences and structures. (5882 citations)
What are the main themes of his work throughout his whole career to date?
Steven E. Brenner mostly deals with Computational biology, Genetics, Genome, Gene and Bioinformatics.
His study in Computational biology is interdisciplinary in nature, drawing from both Proteome, Protein domain, Selection and Protein structure, Structural genomics.
The concepts of his Genome study are interwoven with issues in Disease and Interpretation.
His work in Bioinformatics is not limited to one particular discipline; it also encompasses Set.
His RNA splicing study integrates concerns from other disciplines, such as Alternative splicing and Exon.
While the research belongs to areas of Structural Classification of Proteins database, Steven E. Brenner spends his time largely on the problem of Information retrieval, intersecting his research to questions surrounding Structure.
He most often published in these fields:
- Computational biology (39.08%)
- Genetics (33.72%)
- Genome (19.92%)
What were the highlights of his more recent work (between 2016-2021)?
- Computational biology (39.08%)
- Genome (19.92%)
- Gene (16.86%)
In recent papers he was focusing on the following fields of study:
Steven E. Brenner spends much of his time researching Computational biology, Genome, Gene, Critical assessment and Precision medicine.
Steven E. Brenner has researched Computational biology in several fields, including Cancer, Genomics, Single amino acid, Trait and In silico.
His Genome study is focused on Genetics in general.
His work in the fields of Gene, such as Disease gene, Coding region, Nonsense-mediated decay and Alternative splicing, overlaps with other areas such as Neurological disorder.
His work investigates the relationship between Precision medicine and topics such as Data science that intersect with problems in Profiling.
His Interpretation study frequently draws connections to other fields, such as Bioinformatics.
Between 2016 and 2021, his most popular works were:
- KBase: The United States Department of Energy Systems Biology Knowledgebase. (297 citations)
- Newborn Sequencing in Genomic Medicine and Public Health. (83 citations)
- The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens (82 citations)
In his most recent research, the most cited papers focused on:
His main research concerns Computational biology, Database, Genome, Protein Data Bank and Structural Classification of Proteins database.
His work carried out in the field of Computational biology brings together such families of science as Genetics, Field, Protein structure prediction, CDKN2A and Source code.
His biological study spans a wide range of topics, including Cellular functions and DNA sequencing.
Steven E. Brenner focuses mostly in the field of Genome, narrowing it down to topics relating to Interpretation and, in certain cases, Bioinformatics and Disease.
His research investigates the connection between Bioinformatics and topics such as Data science that intersect with problems in Precision medicine and Exome sequencing.
His Structural Classification of Proteins database study combines topics from a wide range of disciplines, such as Protein domain, Spliceosome and Protein family.
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