What is he best known for?
The fields of study he is best known for:
Daniel J. Gaffney spends much of his time researching Genetics, Chromatin, Gene, Computational biology and Gene expression profiling.
Genetic variation, DNA methylation, Quantitative trait locus, Epigenomics and DNase-Seq are among the areas of Genetics where Daniel J. Gaffney concentrates his study.
His work deals with themes such as Regulation of gene expression and Methylation, which intersect with DNA methylation.
His Chromatin study integrates concerns from other disciplines, such as Lamin, Molecular biology and DNA-binding protein.
His research investigates the link between Computational biology and topics such as Genomics that cross with problems in RNA-Seq, Systems biology and Alternative splicing.
His studies deal with areas such as Expression quantitative trait loci and DNA binding site as well as Gene expression profiling.
His most cited work include:
- A survey of best practices for RNA-seq data analysis (1155 citations)
- DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines. (679 citations)
- DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines. (679 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Genetics, Gene, Computational biology, Quantitative trait locus and Induced pluripotent stem cell.
His study in Gene expression, Human genome, 1000 Genomes Project, DNA methylation and Intron is carried out as part of his studies in Genetics.
His work on Cell biology expands to the thematically related Gene.
Daniel J. Gaffney combines subjects such as RNA-Seq, Phenotype, Genomics, ATAC-seq and Locus with his study of Computational biology.
He has included themes like Chromatin, Expression quantitative trait loci, Genome-wide association study and Genetic variation in his Quantitative trait locus study.
His research integrates issues of Transcription factor and DNA-binding protein in his study of Chromatin.
He most often published in these fields:
- Genetics (64.37%)
- Gene (50.57%)
- Computational biology (35.63%)
What were the highlights of his more recent work (between 2018-2021)?
- Computational biology (35.63%)
- Gene (50.57%)
- Cell (8.05%)
In recent papers he was focusing on the following fields of study:
His main research concerns Computational biology, Gene, Cell, Induced pluripotent stem cell and Locus.
His Computational biology study incorporates themes from Proteome, Genome-wide association study, Human genome, Quantitative trait locus and Enhancer.
His Quantitative trait locus study combines topics from a wide range of disciplines, such as Systems biology and Genomics.
His work on Genome, Phenotype, Somatic cell and DNA sequencing as part of general Gene study is frequently linked to Simple, therefore connecting diverse disciplines of science.
His Induced pluripotent stem cell research focuses on subjects like Expression quantitative trait loci, which are linked to Dopaminergic neuron differentiation and Cell culture.
His Reprogramming study is focused on Genetics in general.
Between 2018 and 2021, his most popular works were:
- N6-methyladenosine regulates the stability of RNA:DNA hybrids in human cells. (46 citations)
- High-resolution genetic mapping of putative causal interactions between regions of open chromatin. (42 citations)
- Souporcell: robust clustering of single-cell RNA-seq data by genotype without reference genotypes (25 citations)
In his most recent research, the most cited papers focused on:
His primary areas of study are Cell biology, Computational biology, RNA, Phagocytosis and Niacin.
His Cell biology research integrates issues from Prostaglandin E2 and Cytokine.
The Computational biology study combines topics in areas such as Transcriptome, Proteomics, Human proteome project, Quantitative trait locus and Induced pluripotent stem cell.
His RNA research includes elements of Base sequence, Lysis, Nucleic acid and Genotype.
His Phagocytosis research is multidisciplinary, incorporating elements of Myelin, Remyelination, CNS demyelination and Multiple sclerosis.
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