What is he best known for?
The fields of study he is best known for:
His main research concerns Cell biology, Computational biology, Genetics, Transcription factor and Gene.
His study in the field of Stem cell and Haematopoiesis is also linked to topics like Nestin.
His study in Computational biology is interdisciplinary in nature, drawing from both Interactive visualization, DNA microarray, Gene expression omnibus and Genome.
Avi Ma'ayan works mostly in the field of Transcription factor, limiting it down to topics relating to Embryonic stem cell and, in certain cases, Downregulation and upregulation, Transcriptome and Epigenetics, as a part of the same area of interest.
His Gene study incorporates themes from Specific protein and Protein–protein interaction.
His work deals with themes such as Web server and Upload, which intersect with Visualization.
His most cited work include:
- Enrichr: a comprehensive gene set enrichment analysis web server 2016 update (2887 citations)
- Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool (2352 citations)
- Mesenchymal and haematopoietic stem cells form a unique bone marrow niche (2327 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Computational biology, Cell biology, Systems biology, Transcription factor and Gene.
His studies in Computational biology integrate themes in fields like Cell signaling, Transcriptome, Gene expression, Proteomics and Visualization.
The concepts of his Cell biology study are interwoven with issues in Embryonic stem cell and Cellular differentiation.
His Transcription factor study combines topics in areas such as Regulation of gene expression and Signal transduction.
His Gene study is related to the wider topic of Genetics.
His Stem cell research is multidisciplinary, relying on both Mesenchymal stem cell and Bone marrow.
He most often published in these fields:
- Computational biology (27.09%)
- Cell biology (23.90%)
- Systems biology (15.14%)
What were the highlights of his more recent work (between 2017-2021)?
- Computational biology (27.09%)
- Cell biology (23.90%)
- Transcription factor (14.34%)
In recent papers he was focusing on the following fields of study:
Avi Ma'ayan mostly deals with Computational biology, Cell biology, Transcription factor, Gene and Transcriptome.
His Computational biology study integrates concerns from other disciplines, such as Cell signaling, Gene expression, Proteomics, Small molecule and Visualization.
The Interactive visualization research he does as part of his general Visualization study is frequently linked to other disciplines of science, such as Context, therefore creating a link between diverse domains of science.
The various areas that Avi Ma'ayan examines in his Cell biology study include Niche and CD8.
His work on RNA-Seq and Gene regulatory network as part of his general Gene study is frequently connected to Repurposing and Set, thereby bridging the divide between different branches of science.
His Stem cell study combines topics from a wide range of disciplines, such as Cell, Mesenchymal stem cell and Bone marrow.
Between 2017 and 2021, his most popular works were:
- Massive mining of publicly available RNA-seq data from human and mouse. (211 citations)
- Unexplored therapeutic opportunities in the human genome. (142 citations)
- Single-cell immune landscape of human atherosclerotic plaques (120 citations)
In his most recent research, the most cited papers focused on:
Computational biology, Gene, Cell biology, Gene expression and Data science are his primary areas of study.
His Computational biology research incorporates themes from Drug response, Cancer drugs, Interactive visualization, Transcriptome and Genome.
His research in Transcriptome tackles topics such as Profiling which are related to areas like Visualization.
His Visualization study combines topics in areas such as Regulation of gene expression and Small molecule.
His Transcription factor and Gene regulatory network study, which is part of a larger body of work in Gene, is frequently linked to Subnetwork and General transcription factor, bridging the gap between disciplines.
He has included themes like Bone marrow and Cell fate determination in his Cell biology study.
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