What is he best known for?
The fields of study he is best known for:
- Gene
- Enzyme
- Internal medicine
His primary areas of study are Cell biology, Biochemistry, Adenylyl cyclase, Signal transduction and G protein.
Ravi Iyengar has researched Cell biology in several fields, including Long-term potentiation, Internal medicine, Receptor and Endocrinology.
Many of his research projects under Receptor are closely connected to Mechanism with Mechanism, tying the diverse disciplines of science together.
His studies deal with areas such as Molecular biology, Protein subunit, GTP' and Guanine as well as Adenylyl cyclase.
His Signal transduction research is multidisciplinary, incorporating perspectives in Autocrine signalling and Protein kinase A, Phosphorylation.
As a part of the same scientific family, he mostly works in the field of GTP-binding protein regulators, focusing on Cell Compartmentation and, on occasion, Computational biology.
His most cited work include:
- Emergent Properties of Networks of Biological Signaling Pathways (1425 citations)
- G Protein Pathways (996 citations)
- Functional atlas of the integrin adhesome (905 citations)
What are the main themes of his work throughout his whole career to date?
Ravi Iyengar focuses on Cell biology, Biochemistry, Adenylyl cyclase, Signal transduction and G protein.
His work carried out in the field of Cell biology brings together such families of science as Receptor and Neurite.
His work in GTP', Glucagon receptor, Guanosine, Binding protein and Peptide is related to Biochemistry.
His study in the field of ADCY9 and Gs alpha subunit is also linked to topics like Hormone receptor.
His Signal transduction study frequently links to related topics such as Phosphorylation.
His research in G protein focuses on subjects like Molecular biology, which are connected to Pertussis toxin.
He most often published in these fields:
- Cell biology (31.16%)
- Biochemistry (20.89%)
- Adenylyl cyclase (18.49%)
What were the highlights of his more recent work (between 2016-2021)?
- Computational biology (13.01%)
- Cell biology (31.16%)
- Cell (6.16%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Computational biology, Cell biology, Cell, Gene and Precision medicine.
The concepts of his Computational biology study are interwoven with issues in Drug action, Proteomics, Disease and Induced pluripotent stem cell.
His work deals with themes such as Neurite and Transcription factor, which intersect with Cell biology.
His Systems biology research focuses on Systems pharmacology and how it connects with Bioinformatics, World Wide Web and Cataloging.
The various areas that Ravi Iyengar examines in his Phenotype study include Copy-number variation, Genomic signature, Signal transduction, Non small cell and Cell shape.
As part of one scientific family, Ravi Iyengar deals mainly with the area of Signal transduction, narrowing it down to issues related to the Cellular differentiation, and often Anatomy.
Between 2016 and 2021, his most popular works were:
- The Library of Integrated Network-Based Cellular Signatures NIH Program: System-Level Cataloging of Human Cells Response to Perturbations (165 citations)
- Modeling susceptibility to drug-induced long QT with a panel of subject-specific induced pluripotent stem cells (47 citations)
- Clinical features of COVID-19 mortality: development and validation of a clinical prediction model (37 citations)
In his most recent research, the most cited papers focused on:
- Gene
- Enzyme
- Internal medicine
His primary areas of investigation include Computational biology, Cell, Precision medicine, Cell culture and Cell biology.
His Systems biology study in the realm of Computational biology connects with subjects such as RNA splicing.
His research integrates issues of Omics data, Transcription factor, Inference and Taxonomy in his study of Cell.
His Cell biology study combines topics in areas such as Phenotype and NFAT.
His Phenotype research integrates issues from Cellular differentiation, Downregulation and upregulation, Mechanotransduction, Signal transduction and Extracellular matrix.
By researching both Signal transduction and Tension, Ravi Iyengar produces research that crosses academic boundaries.
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