H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 32 Citations 4,132 101 World Ranking 7032 National Ranking 3325

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Database
  • Programming language

His primary areas of study are World Wide Web, Genome-wide association study, Genetic association, Single-nucleotide polymorphism and Pacific islanders. His World Wide Web study incorporates themes from Query language and Information retrieval. His research on Genome-wide association study concerns the broader Genetics.

His Genetic association study combines topics from a wide range of disciplines, such as Genetic architecture and Genomics. His work deals with themes such as Population genetics and Allele frequency, which intersect with Single-nucleotide polymorphism. José Luis Ambite interconnects Information integration and Knowledge representation and reasoning in the investigation of issues within Web modeling.

His most cited work include:

  • Genetic analyses of diverse populations improves discovery for complex traits (209 citations)
  • Modeling Web sources for information integration (194 citations)
  • The Ariadne approach to Web- based information integration (181 citations)

What are the main themes of his work throughout his whole career to date?

José Luis Ambite focuses on Information retrieval, Data science, Genome-wide association study, Data integration and World Wide Web. His Data science research integrates issues from Data sharing and Big data. His Genome-wide association study research incorporates elements of SNP, Genetic association and Genomics.

His work carried out in the field of Genetic association brings together such families of science as Genetic epidemiology, Pacific islanders, Bioinformatics and Genetic architecture. As part of his studies on World Wide Web, José Luis Ambite frequently links adjacent subjects like Information integration. His biological study spans a wide range of topics, including RDF and Data mining.

He most often published in these fields:

  • Information retrieval (20.92%)
  • Data science (21.57%)
  • Genome-wide association study (15.69%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (12.42%)
  • Data science (21.57%)
  • Deep learning (3.92%)

In recent papers he was focusing on the following fields of study:

His primary scientific interests are in Artificial intelligence, Data science, Deep learning, Genomics and Machine learning. When carried out as part of a general Artificial intelligence research project, his work on Embedding is frequently linked to work in Process, therefore connecting diverse disciplines of study. In his study, which falls under the umbrella issue of Data science, Field, Biomedicine and Linked data is strongly linked to Big data.

His research on Deep learning also deals with topics like

  • Feature selection and related Linear regression, Autoencoder, Data mining, Logistic regression and Python,
  • Artificial neural network that intertwine with fields like Feature extraction. The concepts of his Genomics study are interwoven with issues in Data access, Genome-wide association study, Computational biology and Knowledge management. José Luis Ambite focuses mostly in the field of Genome-wide association study, narrowing it down to topics relating to Genetic architecture and, in certain cases, Disease.

Between 2018 and 2021, his most popular works were:

  • Genetic analyses of diverse populations improves discovery for complex traits (209 citations)
  • Rapid detection of identity-by-descent tracts for mega-scale datasets (13 citations)
  • Towards a fine-scale population health monitoring system (11 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Database
  • Programming language

José Luis Ambite mainly investigates Genome-wide association study, Genetic association, Disease, Genomics and Artificial intelligence. His Genome-wide association study study improves the overall literature in Single-nucleotide polymorphism. His Genetic association research is multidisciplinary, incorporating perspectives in Health equity, Precision medicine and Genetic architecture.

He has researched Disease in several fields, including Biobank and Population health. His Genomics research includes elements of Chromosome, Computational biology and Pairwise comparison. His Artificial intelligence research includes themes of Domain, Set and Natural language processing.

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.

Top Publications

Modeling Web sources for information integration

Craig A. Knoblock;Steven Minton;José Luis Ambite;Naveen Ashish.
national conference on artificial intelligence (1998)

301 Citations

Semi-automatically mapping structured sources into the semantic web

Craig A. Knoblock;Pedro Szekely;José Luis Ambite;Aman Goel.
international semantic web conference (2012)

237 Citations

Genetic analyses of diverse populations improves discovery for complex traits

Genevieve L. Wojcik;Mariaelisa Graff;Katherine K. Nishimura;Ran Tao.
Nature (2019)

233 Citations

The Ariadne approach to Web- based information integration

Craig A. Knoblock;Steven Minton;Jose Luis Ambite;Naveen Ashish.
International Journal of Cooperative Information Systems (2001)

232 Citations

Web service composition as planning

Mark Carman;Jose Luis Ambite;Luciano Serafini;Craig Knoblock.
ICAPS Workshop on Planning for Web Services (2003)

209 Citations

Integration of heterogeneous knowledge sources in the CALO query manager

José Luis Ambite;Vinay K. Chaudhri;Richard Fikes;Jessica Jenkins.
international conference on move to meaningful internet systems (2005)

171 Citations

Genetic determinants of lipid traits in diverse populations from the population architecture using genomics and epidemiology (PAGE) study.

Logan Dumitrescu;Cara L. Carty;Kira Taylor;Fredrick R. Schumacher.
PLOS Genetics (2011)

162 Citations

Phenome-Wide Association Study (PheWAS) for Detection of Pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network

Sarah A. Pendergrass;Kristin Brown-Gentry;Scott Dudek;Alex Frase.
PLOS Genetics (2013)

160 Citations

Agents for information gathering

J.L. Ambite;C.A. Knoblock.
IEEE Intelligent Systems (1997)

158 Citations

The Next PAGE in Understanding Complex Traits: Design for the Analysis of Population Architecture Using Genetics and Epidemiology (PAGE) Study

Tara C. Matise;Jose Luis Ambite;Steven Buyske;Christopher S. Carlson.
American Journal of Epidemiology (2011)

157 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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Top Scientists Citing José Luis Ambite

Craig A. Knoblock

Craig A. Knoblock

University of Southern California

Publications: 80

Marylyn D. Ritchie

Marylyn D. Ritchie

University of Pennsylvania

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Dana C. Crawford

Dana C. Crawford

Case Western Reserve University

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Kari E. North

Kari E. North

University of North Carolina at Chapel Hill

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Christopher A. Haiman

Christopher A. Haiman

University of Southern California

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Ruth J. F. Loos

Ruth J. F. Loos

Icahn School of Medicine at Mount Sinai

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Charles Kooperberg

Charles Kooperberg

Fred Hutchinson Cancer Research Center

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Eric Boerwinkle

Eric Boerwinkle

The University of Texas Health Science Center at Houston

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Thomas R. Gruber

Thomas R. Gruber

Apple (United States)

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Ulrike Peters

Ulrike Peters

Fred Hutchinson Cancer Research Center

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Joshua C. Denny

Joshua C. Denny

Vanderbilt University Medical Center

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Bruce M. Psaty

Bruce M. Psaty

University of Washington

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Nora Franceschini

Nora Franceschini

University of North Carolina at Chapel Hill

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Tara C. Matise

Tara C. Matise

Rutgers, The State University of New Jersey

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Loic Le Marchand

Loic Le Marchand

University of Hawaii System

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