What is he best known for?
The fields of study Ron Shamir is best known for:
- Gene
- Bipartite graph
- Genome
His research on Gene expression profiling and Gene regulatory network is centered around Gene expression.
He undertakes interdisciplinary study in the fields of Gene and Alternative splicing through his works.
His work often combines Genetics and Genome studies.
He integrates many fields in his works, including Computational biology and Bioinformatics.
He incorporates Bioinformatics and Computational biology in his studies.
Artificial intelligence is frequently linked to Cluster analysis in his study.
Ron Shamir connects Cluster analysis with Data mining in his study.
He merges Data mining with Artificial intelligence in his study.
In most of his Combinatorics studies, his work intersects topics such as Graph.
His most cited work include:
- Clustering Gene Expression Patterns (1076 citations)
- Modelling and analysis of gene regulatory networks (944 citations)
- Network‐based prediction of protein function (908 citations)
What are the main themes of his work throughout his whole career to date
His research on Gene expression, Genome and Transcription factor is centered around Gene.
The study of Gene expression is intertwined with the study of Genetics in a number of ways.
He performs multidisciplinary study in Genetics and Computational biology in his work.
His study deals with a combination of Computational biology and Gene.
In his articles, he combines various disciplines, including Algorithm and Programming language.
His work blends Programming language and Algorithm studies together.
With his scientific publications, his incorporates both Artificial intelligence and Data mining.
He integrates many fields in his works, including Data mining and Artificial intelligence.
He integrates Combinatorics and Discrete mathematics in his research.
Ron Shamir most often published in these fields:
- Genetics (66.97%)
- Gene (62.39%)
- Computational biology (50.00%)
What were the highlights of his more recent work (between 2018-2022)?
- Computational biology (62.50%)
- Genetics (56.25%)
- Gene (50.00%)
In recent works Ron Shamir was focusing on the following fields of study:
His Programming language research incorporates elements of Omics, Bioinformatics and Machine learning, Cluster analysis.
His research on Bioinformatics often connects related areas such as Omics and Personalized medicine.
His study deals with a combination of Machine learning and Cluster analysis.
His Immunology research covers fields of interest such as Immune system and Pathology.
Ron Shamir integrates many fields in his works, including Pathology and Immunology.
He integrates several fields in his works, including Computational biology and Biochemistry.
He merges Biochemistry with Computational biology in his research.
His Sequence (biology) research extends to the thematically linked field of Genetics.
His research brings together the fields of Genetics and Sequence (biology).
Between 2018 and 2022, his most popular works were:
- NEMO: cancer subtyping by integration of partial multi-omic data (98 citations)
- PlasClass improves plasmid sequence classification (46 citations)
- Using the kinetics of C-reactive protein response to improve the differential diagnosis between acute bacterial and viral infections (32 citations)
In his most recent research, the most cited works focused on:
- Gene
- Genome
- Bioinformatics
Ron Shamir connects relevant research areas such as False positive rate and Classifier (UML) in the realm of Artificial intelligence.
His research combines Artificial intelligence and Classifier (UML).
His Virus study is within the categories of Viral load and Viral infection.
He integrates several fields in his works, including Viral load and Virus.
Many of his studies on Viral infection involve topics that are commonly interrelated, such as Immunology.
His work on C-reactive protein expands to the thematically related Immunology.
His Inflammation research includes a combination of various areas of study, such as Differential diagnosis and C-reactive protein.
He performs multidisciplinary study on Differential diagnosis and Inflammation in his works.
By researching both Computational biology and Algorithm, he produces research that crosses academic boundaries.
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