What is he best known for?
The fields of study he is best known for:
His primary areas of investigation include Ataxia, Genetics, Frataxin, Autosomal recessive cerebellar ataxia and Gene.
His Ataxia research includes elements of Mutation, Dystonia and Age of onset.
His research investigates the link between Age of onset and topics such as Genotype that cross with problems in Internal medicine, Central nervous system disease and Endocrinology.
Many of his research projects under Genetics are closely connected to Kelch protein with Kelch protein, tying the diverse disciplines of science together.
In his study, Cerebellar atrophy, Pediatrics and Aprataxin is inextricably linked to Oculomotor apraxia, which falls within the broad field of Autosomal recessive cerebellar ataxia.
His Gene study combines topics from a wide range of disciplines, such as Cataracts, Protein folding, Chaperone and Myopathy.
His most cited work include:
- Friedreich's Ataxia: Autosomal Recessive Disease Caused by an Intronic GAA Triplet Repeat Expansion (2181 citations)
- Aconitase and mitochondrial iron-sulphur protein deficiency in Friedreich ataxia. (850 citations)
- Clinical and Genetic Abnormalities in Patients with Friedreich's Ataxia (816 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Ataxia, Genetics, Cerebellar ataxia, Frataxin and Gene.
Michel Koenig interconnects Missense mutation, Internal medicine and Pediatrics in the investigation of issues within Ataxia.
Locus, Mutation, Allele, Haplotype and Point mutation are the primary areas of interest in his Genetics study.
His research in Locus tackles topics such as Genetic heterogeneity which are related to areas like Disease gene identification.
His Cerebellar ataxia research is multidisciplinary, incorporating elements of Chorea, Age of onset, Movement disorders and Pathology.
His research investigates the connection between Gene and topics such as Computational biology that intersect with problems in DNA sequencing.
He most often published in these fields:
- Ataxia (53.59%)
- Genetics (43.79%)
- Cerebellar ataxia (24.84%)
What were the highlights of his more recent work (between 2016-2021)?
- Ataxia (53.59%)
- Cerebellar ataxia (24.84%)
- Genetics (43.79%)
In recent papers he was focusing on the following fields of study:
Ataxia, Cerebellar ataxia, Genetics, Computational biology and Gene are his primary areas of study.
His Ataxia research includes themes of Missense mutation and Pathology.
His Cerebellar ataxia research incorporates themes from Internal medicine, Atrophy, Age of onset, Movement disorders and Pediatrics.
His Internal medicine research incorporates elements of Dystonia and Endocrinology.
With his scientific publications, his incorporates both Genetics and WWOX.
As a member of one scientific family, Michel Koenig mostly works in the field of Autosomal recessive cerebellar ataxia, focusing on Aprataxin and, on occasion, Polyneuropathy.
Between 2016 and 2021, his most popular works were:
- Assessment of a Targeted Gene Panel for Identification of Genes Associated With Movement Disorders. (29 citations)
- The genetic nomenclature of recessive cerebellar ataxias. (23 citations)
- Dual Molecular Effects of Dominant RORA Mutations Cause Two Variants of Syndromic Intellectual Disability with Either Autism or Cerebellar Ataxia (22 citations)
In his most recent research, the most cited papers focused on:
Michel Koenig spends much of his time researching Cerebellar ataxia, Ataxia, Genetics, Genetic heterogeneity and RNA splicing.
Michel Koenig has researched Cerebellar ataxia in several fields, including Internal medicine, Atrophy, Pathology and Age of onset.
Specifically, his work in Ataxia is concerned with the study of Autosomal recessive cerebellar ataxia.
Genetics is a component of his Genotype, Allele and Locus studies.
His Genetic heterogeneity research integrates issues from Movement disorders and Copy-number variation.
His studies deal with areas such as Duchenne muscular dystrophy and Alternative splicing as well as RNA splicing.
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.
