What is he best known for?
The fields of study he is best known for:
- Gene
- Artificial intelligence
- Statistics
Jesper Tegnér mainly investigates Neuroscience, Genetics, Regulation of gene expression, Computational biology and Gene regulatory network.
The Working memory, Cortex, Prefrontal cortex and Electrophysiology research Jesper Tegnér does as part of his general Neuroscience study is frequently linked to other disciplines of science, such as Spike, therefore creating a link between diverse domains of science.
When carried out as part of a general Genetics research project, his work on DNA methylation, Human genome and Gene is frequently linked to work in Network topology, therefore connecting diverse disciplines of study.
The various areas that Jesper Tegnér examines in his Regulation of gene expression study include Transcription factor, Gene expression, Transcriptional regulation, Cellular differentiation and Coronary artery disease.
The concepts of his Transcriptional regulation study are interwoven with issues in DNA binding site, Molecular biology, Cap analysis gene expression, Protein–protein interaction and Cell fate determination.
Jesper Tegnér combines subjects such as Regression analysis and Bioinformatics with his study of Gene regulatory network.
His most cited work include:
- The Transcriptional Landscape of the Mammalian Genome (2876 citations)
- A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data (812 citations)
- Reverse engineering gene networks using singular value decomposition and robust regression (646 citations)
What are the main themes of his work throughout his whole career to date?
Jesper Tegnér mostly deals with Computational biology, Artificial intelligence, Gene regulatory network, Bioinformatics and Systems biology.
His research in Computational biology intersects with topics in Genetics, Gene expression, Cellular differentiation, Gene and Regulation of gene expression.
His Cellular differentiation research is multidisciplinary, incorporating elements of Self-organizing map, Chromatin and Cell biology.
His studies in Regulation of gene expression integrate themes in fields like Transcription factor and Gene expression profiling.
Jesper Tegnér conducts interdisciplinary study in the fields of Gene regulatory network and Reverse engineering through his research.
His work carried out in the field of Systems biology brings together such families of science as Personalized medicine and Data science.
He most often published in these fields:
- Computational biology (37.56%)
- Artificial intelligence (15.03%)
- Gene regulatory network (21.24%)
What were the highlights of his more recent work (between 2018-2021)?
- Computational biology (37.56%)
- Artificial intelligence (15.03%)
- Multi omics (9.84%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Computational biology, Artificial intelligence, Multi omics, Cell biology and Cancer research.
His Computational biology study combines topics in areas such as RNA-Seq, Proteomics, Chromatin, Messenger RNA and splice.
His research on Multi omics also deals with topics like
- Parametric statistics which intersects with area such as Glioblastoma and Profiling,
- Metabolomics that connect with fields like Omics technologies, Cell physiology and Gene expression.
The Cancer research study combines topics in areas such as Kynurenine pathway, DNA methylation, T cell, Multiple sclerosis and Epigenetics.
In his work, Regulation of gene expression is strongly intertwined with Cell cycle, which is a subfield of Cellular differentiation.
His research integrates issues of Self-organizing map and Genome in his study of Gene regulatory network.
Between 2018 and 2021, his most popular works were:
- Causal deconvolution by algorithmic generative models (30 citations)
- Causal deconvolution by algorithmic generative models (30 citations)
- Causal deconvolution by algorithmic generative models (30 citations)
In his most recent research, the most cited papers focused on:
- Gene
- Artificial intelligence
- Statistics
His primary areas of investigation include Cellular differentiation, Gene regulatory network, Cellular automaton, Data type and Computational biology.
The study incorporates disciplines such as Regulation of gene expression, Multi omics and Adaptation in addition to Cellular differentiation.
His Regulation of gene expression study integrates concerns from other disciplines, such as Developmental biology, Cell biology, Transcription factor and Housekeeping gene.
He interconnects Complex system, Biological network, Systems biology and Phase space in the investigation of issues within Gene regulatory network.
As a part of the same scientific study, Jesper Tegnér usually deals with the Cellular automaton, concentrating on Dynamical systems theory and frequently concerns with Complex network, Theoretical computer science, Algorithmic information theory and Calculus.
His study in Computational biology is interdisciplinary in nature, drawing from both RNA-Seq, Proteomics, Metabolomics and Genomics.
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