What is he best known for?
The fields of study he is best known for:
His primary areas of study are Genetics, Phylogenetics, Phylogenetic tree, Mega- and Molecular clock.
His study looks at the intersection of Genetics and topics like Evolutionary biology with Biodiversity, Diversification, Bayesian probability and Primate.
His Phylogenetics research is multidisciplinary, incorporating elements of Zoology, Inference, Mitochondrial DNA, Genomics and Tree.
The Phylogenetic tree study combines topics in areas such as Sequence, Statistics and Transversion.
Mega- combines with fields such as Software, Theoretical computer science, Human evolutionary genetics and Bioinformatics in his work.
His work carried out in the field of Software brings together such families of science as Graphical user interface and Cross-platform.
His most cited work include:
- MEGA5: Molecular Evolutionary Genetics Analysis using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods (34136 citations)
- MEGA6: Molecular Evolutionary Genetics Analysis Version 6.0 (30395 citations)
- MEGA6: Molecular Evolutionary Genetics Analysis Version 6.0 (30395 citations)
What are the main themes of his work throughout his whole career to date?
Sudhir Kumar mainly focuses on Genetics, Computational biology, Phylogenetics, Gene and Evolutionary biology.
His Genetics study is mostly concerned with Genome and Mutation.
His Computational biology study frequently draws connections between related disciplines such as Gene expression profiling.
Phylogenetics and Phylogenetic tree are frequently intertwined in his study.
His Gene research focuses on Gene expression in particular.
He most often published in these fields:
- Genetics (17.42%)
- Computational biology (14.04%)
- Phylogenetics (10.81%)
What were the highlights of his more recent work (between 2019-2021)?
- Computational biology (14.04%)
- Evolutionary biology (9.69%)
- Bayesian probability (5.76%)
In recent papers he was focusing on the following fields of study:
Sudhir Kumar mainly investigates Computational biology, Evolutionary biology, Bayesian probability, Divergence and Phylogenetics.
His Computational biology study combines topics from a wide range of disciplines, such as Selection, Clone, Genetic linkage, Gene and Exome.
His Divergence research integrates issues from Machine learning, Sequence, Molecular clock and Artificial intelligence.
His work deals with themes such as Cancer, Phylogenetic tree and Bayesian inference, which intersect with Phylogenetics.
His Prior probability study combines topics in areas such as Data mining, Graphical user interface, Inference, Tree and Software.
Sudhir Kumar undertakes interdisciplinary study in the fields of Inference and Mega- through his research.
Between 2019 and 2021, his most popular works were:
- Molecular Evolutionary Genetics Analysis (MEGA) for macOS. (245 citations)
- Molecular Evolutionary Genetics Analysis (MEGA) for macOS. (245 citations)
- Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis (57 citations)
In his most recent research, the most cited papers focused on:
His primary scientific interests are in Bayesian probability, Evolutionary biology, Divergence, Computational biology and Prior probability.
His studies in Evolutionary biology integrate themes in fields like Phylogenetics and Phylogenetic tree.
His Phylogenetics research is multidisciplinary, relying on both Genome and Disease.
His research in Computational biology intersects with topics in Sequencing data, Mutation, Gene, Somatic cell and Selection.
The various areas that Sudhir Kumar examines in his Prior probability study include Sequence, Data mining and Inference.
His studies in Data mining integrate themes in fields like Graphical user interface and Software.
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