What is he best known for?
The fields of study he is best known for:
- Algorithm
- Artificial intelligence
- Gene
His primary areas of study are Genetics, Combinatorics, Approximate string matching, Edit distance and String.
His Combinatorics research incorporates elements of Generalized suffix tree and Longest common substring problem.
His study looks at the relationship between Generalized suffix tree and topics such as Compressed suffix array, which overlap with Suffix automaton and Suffix array.
Esko Ukkonen has researched Approximate string matching in several fields, including String-to-string correction problem and String searching algorithm.
Esko Ukkonen combines subjects such as Discrete mathematics and Algorithm with his study of String.
His Transcription factor study combines topics in areas such as DNA microarray, Chromatin immunoprecipitation and Binding site.
His most cited work include:
- On-line construction of suffix trees (1285 citations)
- DNA-Binding Specificities of Human Transcription Factors (803 citations)
- Approximate string-matching with q -grams and maximal matches (553 citations)
What are the main themes of his work throughout his whole career to date?
Esko Ukkonen mainly investigates Combinatorics, Algorithm, Discrete mathematics, Theoretical computer science and String searching algorithm.
His Combinatorics research is multidisciplinary, incorporating elements of String, Edit distance and Pattern matching.
His research in String intersects with topics in Finite-state machine and Set.
His Dynamic programming study in the realm of Algorithm connects with subjects such as Sequence.
His Discrete mathematics research is multidisciplinary, incorporating perspectives in Deterministic pushdown automaton and Heuristics.
He works mostly in the field of String searching algorithm, limiting it down to topics relating to Approximate string matching and, in certain cases, String-to-string correction problem.
He most often published in these fields:
- Combinatorics (26.73%)
- Algorithm (20.74%)
- Discrete mathematics (17.05%)
What were the highlights of his more recent work (between 2006-2020)?
- Algorithm (20.74%)
- Combinatorics (26.73%)
- Genetics (10.14%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Algorithm, Combinatorics, Genetics, Transcription factor and Artificial intelligence.
His work carried out in the field of Algorithm brings together such families of science as Sequence database, Set and Pattern matching.
His work in Pattern matching covers topics such as Time complexity which are related to areas like Substring.
His study in Combinatorics is interdisciplinary in nature, drawing from both Discrete mathematics, Longest repeated substring problem, Longest common substring problem and Variable length.
His Discrete mathematics study incorporates themes from Optimization problem, Decision problem and String.
His studies in Transcription factor integrate themes in fields like DNA and Binding site.
Between 2006 and 2020, his most popular works were:
- DNA-Binding Specificities of Human Transcription Factors (803 citations)
- The common colorectal cancer predisposition SNP rs6983267 at chromosome 8q24 confers potential to enhanced Wnt signaling (430 citations)
- Genome-Wide Analysis of ETS-Family DNA-Binding In Vitro and In Vivo (424 citations)
In his most recent research, the most cited papers focused on:
- Algorithm
- Artificial intelligence
- Gene
Esko Ukkonen mainly focuses on Genetics, Transcription factor, Genome, Algorithm and Software.
Many of his research projects under Genetics are closely connected to Lepidoptera genitalia with Lepidoptera genitalia, tying the diverse disciplines of science together.
Esko Ukkonen has included themes like Chromatin immunoprecipitation, DNA, DNA microarray, Allele and Binding site in his Transcription factor study.
The various areas that Esko Ukkonen examines in his Genome study include Computational biology and Karyotype.
His study in Algorithm is interdisciplinary in nature, drawing from both Nanopore sequencing, Set, Position-Specific Scoring Matrices and Word error rate.
His Software research is multidisciplinary, relying on both Graph, Theoretical computer science, Source code, Documentation and Workflow.
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