What is he best known for?
The fields of study he is best known for:
- Gene
- DNA
- Internal medicine
His primary areas of investigation include Genetics, Endocrinology, Internal medicine, Neuropeptide Y receptor and Gene.
His work on Computational biology expands to the thematically related Genetics.
His work carried out in the field of Internal medicine brings together such families of science as CREB and Sensitization.
Claes Wahlestedt is interested in Antisense RNA, which is a field of Gene.
His Antisense RNA study integrates concerns from other disciplines, such as RNA interference and Sense.
His Regulation of gene expression study combines topics in areas such as RNA, Non-coding RNA, microRNA and Cell biology.
His most cited work include:
- The Transcriptional Landscape of the Mammalian Genome (2876 citations)
- Antisense Transcription in the Mammalian Transcriptome (1437 citations)
- Antisense Transcription in the Mammalian Transcriptome (1437 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Internal medicine, Genetics, Endocrinology, Gene and Neuropeptide Y receptor.
His work in Genetics tackles topics such as Computational biology which are related to areas like Oligonucleotide.
The concepts of his Endocrinology study are interwoven with issues in Neuropeptide and Substance P.
His Gene study is mostly concerned with Gene expression, ENCODE and Transcriptome.
Claes Wahlestedt interconnects Chromatin, Epigenetics and Long non-coding RNA in the investigation of issues within Gene expression.
His work in RNA addresses issues such as Molecular biology, which are connected to fields such as Messenger RNA, Cell biology, Gene knockdown, DNA and Biochemistry.
He most often published in these fields:
- Internal medicine (23.42%)
- Genetics (25.34%)
- Endocrinology (21.49%)
What were the highlights of his more recent work (between 2013-2021)?
- Epigenetics (11.57%)
- Cancer research (6.89%)
- Gene expression (9.09%)
In recent papers he was focusing on the following fields of study:
His main research concerns Epigenetics, Cancer research, Gene expression, Bromodomain and Genetics.
His Epigenetics study deals with Histone intersecting with Cell biology, Acetylation and Genome.
His studies deal with areas such as Web application, Interactive visualization, Visualization, Downregulation and upregulation and Regulation of gene expression as well as Gene expression.
His work on Genetics deals in particular with Gene, Long non-coding RNA, Trinucleotide repeat expansion, FMR1 and Histone methylation.
His studies examine the connections between Gene and genetics, as well as such issues in Computational biology, with regards to ENCODE.
Claes Wahlestedt works on RNA which deals in particular with Antisense RNA.
Between 2013 and 2021, his most popular works were:
- The Landscape of long noncoding RNA classification (520 citations)
- Non-coding RNAs as direct and indirect modulators of epigenetic regulation. (275 citations)
- Altering the course of schizophrenia: progress and perspectives (238 citations)
In his most recent research, the most cited papers focused on:
- Gene
- DNA
- Internal medicine
Claes Wahlestedt mainly investigates Cancer research, Epigenetics, Genetics, Bromodomain and RNA.
His research on Epigenetics also deals with topics like
- Chromatin immunoprecipitation, which have a strong connection to Histone methylation,
- Histone and related Conditioned place preference and Nucleus accumbens,
- Alcohol dependence that connect with fields like Gene knockdown, Endocrinology, Psychopharmacology, Ethanol and Neuroscience.
The study incorporates disciplines such as Gene expression and Bioinformatics in addition to RNA.
In his study, Alzheimer's disease is inextricably linked to Regulation of gene expression, which falls within the broad field of Gene expression.
His Long non-coding RNA research incorporates elements of Annotation, RNA interference, Computational biology and Transcriptome.
His Antisense RNA study necessitates a more in-depth grasp of Transcription.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
