What is he best known for?
The fields of study he is best known for:
Quaid Morris focuses on Genetics, Gene, Computational biology, RNA and Genome.
His work on Regulation of gene expression, Exon, Intron and Human genome as part of general Gene study is frequently connected to Synthetic genetic array, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
Quaid Morris has included themes like Carcinogenesis, DNA microarray, Molecular evolution and Gene regulatory network in his Computational biology study.
His research investigates the link between Gene regulatory network and topics such as Bioinformatics that cross with problems in Interactome.
Quaid Morris usually deals with RNA and limits it to topics linked to Messenger RNA and Biotinylation.
The study incorporates disciplines such as Germline mutation, In vitro, Model organism, Function and Human genetics in addition to Genome.
His most cited work include:
- The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. (1855 citations)
- The genetic landscape of a cell. (1828 citations)
- A compendium of RNA-binding motifs for decoding gene regulation (923 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Genetics, Computational biology, Gene, Gene expression and Genome.
His research related to RNA, microRNA, Regulation of gene expression, Gene expression profiling and Binding site might be considered part of Genetics.
His research in Computational biology intersects with topics in Cancer, Bioinformatics, Mutation, RNA-binding protein and DNA sequencing.
His work deals with themes such as RNA splicing and Cell biology, which intersect with RNA-binding protein.
In general Gene study, his work on Phenotype, Gene regulatory network and Functional genomics often relates to the realm of Set, thereby connecting several areas of interest.
His biological study spans a wide range of topics, including Tumor heterogeneity, Human cancer and Cancer type.
He most often published in these fields:
- Genetics (35.85%)
- Computational biology (33.02%)
- Gene (24.53%)
What were the highlights of his more recent work (between 2018-2021)?
- Computational biology (33.02%)
- Genome (15.57%)
- Cancer (11.79%)
In recent papers he was focusing on the following fields of study:
His main research concerns Computational biology, Genome, Cancer, Mutation and Gene.
His Computational biology research is multidisciplinary, relying on both Phylogenetic tree, Function, Mutation detection, DNA sequencing and Binding selectivity.
His Genome research incorporates elements of Tumor heterogeneity, Cancer type, Transcription factor and Germline mutation.
Quaid Morris studied Mutation and Allele frequency that intersect with Human genome and Neutral mutation.
Gene is a primary field of his research addressed under Genetics.
His work on Endocytosis, Single-cell analysis, Penetrance and High-content screening as part of general Genetics research is frequently linked to Lysosome, bridging the gap between disciplines.
Between 2018 and 2021, his most popular works were:
- Pan-cancer analysis of whole genomes (538 citations)
- The evolutionary history of 2,658 cancers (220 citations)
- Similarity regression predicts evolution of transcription factor sequence specificity. (36 citations)
In his most recent research, the most cited papers focused on:
His primary areas of study are Genome, Computational biology, RNA-binding protein, Cancer research and Internal medicine.
In general Genome, his work in Whole genome sequencing is often linked to C2H2 Zinc Finger linking many areas of study.
His work carried out in the field of Computational biology brings together such families of science as Tumor heterogeneity, Germline mutation, Conserved sequence and Regulation of gene expression.
Quaid Morris has researched RNA-binding protein in several fields, including RNA splicing, Gene knockdown and Cell biology.
His Internal medicine research is multidisciplinary, incorporating perspectives in Text mining, Deep learning, Artificial intelligence and ENCODE.
His RNA study introduces a deeper knowledge of Gene.
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