What is he best known for?
The fields of study he is best known for:
Rama Ranganathan mainly focuses on Biochemistry, Statistical coupling analysis, Protein structure, Binding site and Peptide sequence.
Biochemistry and Cell biology are frequently intertwined in his study.
His study on Arrestin is often connected to Retinoid X receptor as part of broader study in Cell biology.
His Statistical coupling analysis research integrates issues from Amino acid, Protein tertiary structure, Computational biology and Protein family.
His work carried out in the field of Protein structure brings together such families of science as Allosteric regulation and KcsA potassium channel.
His Binding site study combines topics in areas such as Biophysics and PDZ domain.
His most cited work include:
- Evolutionarily conserved pathways of energetic connectivity in protein families. (1087 citations)
- Evolutionarily conserved networks of residues mediate allosteric communication in proteins (682 citations)
- Structural and Functional Analysis of the Mitotic Rotamase Pin1 Suggests Substrate Recognition Is Phosphorylation Dependent (578 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Computational biology, Cell biology, Statistical coupling analysis, Biochemistry and Protein structure.
His Computational biology research incorporates elements of Epistasis and Genetics, Function.
His Cell biology research is multidisciplinary, incorporating perspectives in Retinal degeneration and Visual phototransduction.
The various areas that Rama Ranganathan examines in his Statistical coupling analysis study include Amino acid, Protein tertiary structure, Protein family, Folding and Peptide sequence.
His Conserved sequence, G protein and Dihydrofolate reductase study in the realm of Biochemistry connects with subjects such as Protein engineering.
His Protein structure research includes elements of Plasma protein binding, Protein methods, Protein folding, Allosteric regulation and Binding site.
He most often published in these fields:
- Computational biology (31.40%)
- Cell biology (24.42%)
- Statistical coupling analysis (20.93%)
What were the highlights of his more recent work (between 2016-2021)?
- Computational biology (31.40%)
- Epistasis (6.98%)
- Coevolution (5.81%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Computational biology, Epistasis, Coevolution, Amino acid and Systems biology.
The study incorporates disciplines such as Statistical coupling analysis, Protein kinase domain and Function in addition to Computational biology.
His study focuses on the intersection of Statistical coupling analysis and fields such as Sequence analysis with connections in the field of Cooperativity, Chemical biology, Pairwise comparison and Protein superfamily.
His biological study spans a wide range of topics, including Genotype-phenotype distinction, Fluorescent protein, Multiple sequence alignment and A protein.
His Systems biology study integrates concerns from other disciplines, such as Lineage, Cell signaling and GTPase-activating protein.
His study brings together the fields of Cell biology and Genetics.
Between 2016 and 2021, his most popular works were:
- Coevolution-based inference of amino acid interactions underlying protein function (57 citations)
- Deconstruction of the Ras switching cycle through saturation mutagenesis (47 citations)
- An evolutionary hotspot defines functional differences between CRYPTOCHROMES. (36 citations)
In his most recent research, the most cited papers focused on:
The scientist’s investigation covers issues in Computational biology, Epistasis, Systems biology, Genetics and A protein.
The concepts of his Computational biology study are interwoven with issues in Function and Rational design.
Rama Ranganathan interconnects Amino acid, Cooperativity, Chemical biology, Coevolution and Sequence analysis in the investigation of issues within Epistasis.
The Systems biology study combines topics in areas such as Saturated mutagenesis, Mutation, Statistical coupling analysis and Structural biology, Cell biology.
His study in the fields of Allosteric regulation, Kinase, Cancer mutations and ENCODE under the domain of Genetics overlaps with other disciplines such as Hierarchical organization.
His research investigates the connection with A protein and areas like Genotype-phenotype distinction which intersect with concerns in Epistasis and functional genomics and Sequence space.
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