What is he best known for?
The fields of study Dan Geiger is best known for:
As a part of the same scientific study, Dan Geiger usually deals with the Exponential function, concentrating on Mathematical analysis and frequently concerns with Completeness (order theory), Domain (mathematical analysis) and Generalization.
Dan Geiger integrates Domain (mathematical analysis) with Mathematical analysis in his research.
Dan Geiger performs multidisciplinary study on Generalization and Inference in his works.
Dan Geiger integrates many fields in his works, including Inference and Knowledge representation and reasoning.
Dan Geiger carries out multidisciplinary research, doing studies in Genetics and Cancer research.
In his works, he performs multidisciplinary study on Cancer research and Genetics.
In his works, Dan Geiger conducts interdisciplinary research on Gene and ENCODE.
As part of his studies on Artificial intelligence, he often connects relevant subjects like Perspective (graphical).
His Perspective (graphical) study frequently draws connections to other fields, such as Artificial intelligence.
His most cited work include:
- None (4054 citations)
- None (1770 citations)
- Learning Bayesian networks: The combination of knowledge and statistical data (1097 citations)
What are the main themes of his work throughout his whole career to date
Many of his studies on Artificial intelligence involve topics that are commonly interrelated, such as Bayesian network, Bayesian probability and Inference.
He conducts interdisciplinary study in the fields of Inference and Artificial intelligence through his works.
Dan Geiger connects relevant research areas such as Independence (probability theory), Bayesian network and Bayesian probability in the realm of Statistics.
In his works, he undertakes multidisciplinary study on Independence (probability theory) and Statistics.
He integrates many fields in his works, including Genetics and Computational biology.
Computational biology and Genetics are two areas of study in which Dan Geiger engages in interdisciplinary work.
Dan Geiger incorporates Gene and Locus (genetics) in his studies.
His multidisciplinary approach integrates Algorithm and Machine learning in his work.
He integrates Machine learning with Algorithm in his study.
Dan Geiger most often published in these fields:
- Genetics (51.39%)
- Gene (50.00%)
- Artificial intelligence (47.22%)
What were the highlights of his more recent work (between 2017-2021)?
- Genetics (75.00%)
- Gene (75.00%)
- Statistics (50.00%)
In recent works Dan Geiger was focusing on the following fields of study:
As part of his studies on Genetics, Dan Geiger often connects relevant subjects like Missense mutation.
Dan Geiger integrates Missense mutation and Mutation in his research.
Dan Geiger performs multidisciplinary study in Mutation and Phenotype in his work.
His study deals with a combination of Phenotype and Penetrance.
In his works, he undertakes multidisciplinary study on Penetrance and Gene.
Dan Geiger performs multidisciplinary study in Gene and Inheritance (genetic algorithm) in his work.
His research on Inheritance (genetic algorithm) frequently links to adjacent areas such as Genetics.
He performs integrative study on Statistics and Applied mathematics.
Dan Geiger integrates Applied mathematics with Statistics in his research.
Between 2017 and 2021, his most popular works were:
- Quantitative analysis of population-scale family trees with millions of relatives (132 citations)
- Parameter priors for directed acyclic graphical models and the characterization of several probability distributions (67 citations)
- Fatal thoracic aortic aneurysm and dissection in a large family with a novel MYLK gene mutation: delineation of the clinical phenotype (14 citations)
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