H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 38 Citations 6,824 237 World Ranking 4906 National Ranking 31

Research.com Recognitions

Awards & Achievements

2006 - IEEE Fellow For contributions to natural language systems and bioinformatics.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Gene

Wen-Lian Hsu mostly deals with Artificial intelligence, Combinatorics, Computational biology, Discrete mathematics and Genetics. He combines subjects such as Machine learning, Named-entity recognition and Natural language processing with his study of Artificial intelligence. The Natural language processing study combines topics in areas such as Controlled vocabulary and Information retrieval.

His studies in Combinatorics integrate themes in fields like Algorithm and Matrix. His study in Computational biology is interdisciplinary in nature, drawing from both Peptide sequence, Glycoprotein and Resource. His research in Annotation intersects with topics in Protein function prediction, Human Phenotype Ontology, Set and Data set.

His most cited work include:

  • miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions. (911 citations)
  • miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database (847 citations)
  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy (241 citations)

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

His primary areas of investigation include Artificial intelligence, Natural language processing, Information retrieval, Combinatorics and Algorithm. His study of Conditional random field is a part of Artificial intelligence. He has included themes like Named-entity recognition and Word, Text segmentation in his Natural language processing study.

He mostly deals with Question answering in his studies of Information retrieval. His research on Combinatorics often connects related topics like Discrete mathematics. His research integrates issues of Clique-sum and Strong perfect graph theorem in his study of Chordal graph.

He most often published in these fields:

  • Artificial intelligence (47.06%)
  • Natural language processing (33.96%)
  • Information retrieval (15.51%)

What were the highlights of his more recent work (between 2015-2021)?

  • Artificial intelligence (47.06%)
  • Natural language processing (33.96%)
  • Computational biology (8.29%)

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

Wen-Lian Hsu mostly deals with Artificial intelligence, Natural language processing, Computational biology, Sentiment analysis and Machine learning. His research is interdisciplinary, bridging the disciplines of Context and Artificial intelligence. His Natural language processing research includes themes of Embedding, Speech recognition, Tree structure, Named-entity recognition and Kernel.

His biological study spans a wide range of topics, including Proteomics, Genome, Similarity, Personal genomics and Protein sequencing. His Machine learning research is multidisciplinary, incorporating perspectives in Protein function prediction, Human Phenotype Ontology, Set and Data set. His Database study combines topics from a wide range of disciplines, such as Software and MiRTarBase.

Between 2015 and 2021, his most popular works were:

  • miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions. (911 citations)
  • miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database (847 citations)
  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy (241 citations)

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

  • Artificial intelligence
  • Machine learning
  • Gene

Wen-Lian Hsu spends much of his time researching Artificial intelligence, Annotation, Computational biology, Field and Information retrieval. His Artificial intelligence study combines topics in areas such as Machine learning and Natural language processing. His work carried out in the field of Machine learning brings together such families of science as Protein function prediction, Human Phenotype Ontology and Set.

His research investigates the connection with Annotation and areas like Named-entity recognition which intersect with concerns in Relationship extraction, Interoperability, Usability, XML and Learning classifier system. His Computational biology study incorporates themes from Database search engine, Magic and Resource. Wen-Lian Hsu interconnects Context, Computational intelligence and World Wide Web, Data curation in the investigation of issues within Information retrieval.

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.

Best Publications

miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions.

Chih-Hung Chou;Sirjana Shrestha;Chi-Dung Yang;Chi-Dung Yang;Nai-Wen Chang.
Nucleic Acids Research (2018)

1120 Citations

miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database

Chih Hung Chou;Nai Wen Chang;Sirjana Shrestha;Sheng Da Hsu.
Nucleic Acids Research (2016)

949 Citations

On the General Feasibility Test of Scheduling Lot Sizes for Several Products on One Machine

 Wen-Lian Hsu.
Management Science (1983)

303 Citations

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Yuxiang Jiang;Tal Ronnen Oron;Wyatt T Clark;Asma R Bankapur.
arXiv: Quantitative Methods (2016)

278 Citations

Easy and hard bottleneck location problems

Wen-Lian Hsu;George L. Nemhauser.
Discrete Applied Mathematics (1979)

242 Citations

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur.
Genome Biology (2016)

242 Citations

The sustainability balanced scorecard as a framework for selecting socially responsible investment: an effective MCDM model

W.-H. Tsai;W.-C. Chou;W. Hsu.
Journal of the Operational Research Society (2009)

190 Citations

Recognizing circle graphs in polynomial time

Csaba P. Gabor;Kenneth J. Supowit;Wen-Lian Hsu.
Journal of the ACM (1989)

163 Citations

The measurement of user satisfaction with question answering systems

Chorng-Shyong Ong;Min-Yuh Day;Wen-Lian Hsu.
Information & Management (2009)

142 Citations

NERBio: using selected word conjunctions, term normalization, and global patterns to improve biomedical named entity recognition

Richard Tzong-Han Tsai;Cheng-Lung Sung;Hong-Jie Dai;Hsieh-Chuan Hung.
BMC Bioinformatics (2006)

141 Citations

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