What is he best known for?
The fields of study he is best known for:
Genetics, Genome, Genomics, Computational biology and Proteomics are his primary areas of study.
The various areas that Vineet Bafna examines in his Genome study include Metaphase, Haplotype and DNA sequencing.
His Genomics study incorporates themes from Genome-wide association study, Genetic variability, Genetic association, 1000 Genomes Project and Data set.
His study in Computational biology is interdisciplinary in nature, drawing from both Shotgun sequencing, Bioinformatics, Protein family, Base pair and Sequence.
The study incorporates disciplines such as Genome evolution, Genome project, Gene density, Genome size and Nonsynonymous substitution in addition to Reference genome.
His Gene density research is multidisciplinary, incorporating perspectives in Sequence-tagged site and Hybrid genome assembly.
His most cited work include:
- The sequence of the human genome. (10608 citations)
- A global reference for human genetic variation. (7825 citations)
- The Diploid Genome Sequence of an Individual Human (1586 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Computational biology, Genetics, Genome, Genomics and Haplotype.
His Computational biology research incorporates themes from Structural variation, Bioinformatics, Proteomics, Sequence and Mass spectrometry.
His work deals with themes such as Proteogenomics and Gene prediction, which intersect with Proteomics.
His research related to Human genome, Gene, DNA sequencing, Genome-wide association study and Allele might be considered part of Genetics.
Vineet Bafna has included themes like Proteome, Data mining and Human genetics in his Genome study.
His Haplotype research is multidisciplinary, relying on both Evolutionary biology and Single-nucleotide polymorphism.
He most often published in these fields:
- Computational biology (37.40%)
- Genetics (34.96%)
- Genome (30.08%)
What were the highlights of his more recent work (between 2017-2021)?
- Computational biology (37.40%)
- Genome (30.08%)
- Extrachromosomal DNA (7.32%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Computational biology, Genome, Extrachromosomal DNA, Cancer and Cancer research.
His Computational biology research is multidisciplinary, incorporating elements of Genomics, Optical mapping, Human genetics and Human genome.
His biological study spans a wide range of topics, including Data mining and Identification.
His Cancer research includes themes of Amplicon and Whole genome sequencing.
His Gene study contributes to a more complete understanding of Genetics.
His Genetics study frequently draws connections to other fields, such as Pathogenesis.
Between 2017 and 2021, his most popular works were:
- Circular ecDNA promotes accessible chromatin and high oncogene expression (80 citations)
- Extrachromosomal oncogene amplification in tumour pathogenesis and evolution. (60 citations)
- NAD metabolic dependency in cancer is shaped by gene amplification and enhancer remodelling (49 citations)
In his most recent research, the most cited papers focused on:
His main research concerns Computational biology, Extrachromosomal DNA, Genome, Cancer and Cancer research.
His studies in Computational biology integrate themes in fields like Metaproteomics, Tandem mass spectrum, Underlying disease and Genomics.
His research in Genomics intersects with topics in Nucleic acid amplification technique, Selection, Selective sweep and Population genetics.
Vineet Bafna interconnects Transcription, Human genetics and Intratumoral Genetic Heterogeneity in the investigation of issues within Extrachromosomal DNA.
His Genome study combines topics from a wide range of disciplines, such as Identification and DNA barcoding.
His work carried out in the field of DNA barcoding brings together such families of science as Identification, DNA sequencing, Reference genome, Environmental DNA and Sample.
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