H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 38 Citations 15,701 169 World Ranking 5001 National Ranking 467

Overview

What is he best known for?

The fields of study he is best known for:

  • Algorithm
  • Artificial intelligence
  • Gene

Tak-Wah Lam mostly deals with Genome, Parallel computing, DNA sequencing, Computational biology and Sequence assembly. Genome is often connected to Data mining in his work. His work on Parallel algorithm as part of general Parallel computing research is frequently linked to Ultra fast, thereby connecting diverse disciplines of science.

His Computational biology research integrates issues from Whole genome sequencing and Sequence. His studies in Sequence assembly integrate themes in fields like Contig and Genomics. His biological study spans a wide range of topics, including Algorithm design and Error detection and correction.

His most cited work include:

  • SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler (3123 citations)
  • SOAP2: an improved ultrafast tool for short read alignment. (2900 citations)
  • MEGAHIT: An ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph (1444 citations)

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

His primary areas of investigation include Combinatorics, Algorithm, Competitive analysis, Time complexity and Online algorithm. His Combinatorics research is multidisciplinary, relying on both Matching, Discrete mathematics, Data structure and Pattern matching. The concepts of his Algorithm study are interwoven with issues in Sequence and Speedup.

His work investigates the relationship between Competitive analysis and topics such as Distributed computing that intersect with problems in Dynamic priority scheduling. In his work, Theoretical computer science and Space is strongly intertwined with Set, which is a subfield of Time complexity. His Online algorithm course of study focuses on Parallel computing and Multiprocessor scheduling.

He most often published in these fields:

  • Combinatorics (24.81%)
  • Algorithm (21.48%)
  • Competitive analysis (15.56%)

What were the highlights of his more recent work (between 2014-2021)?

  • Computational biology (11.11%)
  • Artificial intelligence (6.30%)
  • Genomics (5.19%)

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

Tak-Wah Lam focuses on Computational biology, Artificial intelligence, Genomics, Nanopore sequencing and Data mining. His studies deal with areas such as Regulation of gene expression, DNA sequencing, Gene, Reference genome and Signal transduction as well as Computational biology. His Artificial intelligence study combines topics in areas such as Natural language processing, Source code, Sequence assembly and Pattern recognition.

His research on Genomics concerns the broader Genome. His research integrates issues of Effective method and Computer engineering in his study of Genome. Tak-Wah Lam has included themes like Construct, Software and Multiple sequence alignment in his Data mining study.

Between 2014 and 2021, his most popular works were:

  • MEGAHIT: An ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph (1444 citations)
  • MEGAHIT v1.0: A fast and scalable metagenome assembler driven by advanced methodologies and community practices (397 citations)
  • Erratum to "SOAPdenovo2: An empirically improved memory-efficient short-read de novo assembler" [GigaScience, (2012), 1, 18] (116 citations)

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

  • Artificial intelligence
  • Algorithm
  • Gene

His primary areas of study are Genomics, Artificial neural network, Computational biology, Parallel computing and Nanopore sequencing. His Genomics study deals with the bigger picture of Genome. The Computational biology study which covers DNA sequencing that intersects with Task, Allele and Zygosity.

His study in the field of Speedup also crosses realms of Single node. His Nanopore sequencing research incorporates themes from Germline, Sequence assembly, Limit, Machine learning and Central processing unit. His study looks at the intersection of Software and topics like Scalability with Parallel algorithm, Memory footprint and De Bruijn sequence.

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

SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler

Ruibang Luo;Binghang Liu;Yinlong Xie;Yinlong Xie;Zhenyu Li.
GigaScience (2012)

3602 Citations

SOAP2: an improved ultrafast tool for short read alignment.

Ruiqiang Li;Chang Yu;Yingrui Li;Tak Wah Lam.
Bioinformatics (2009)

3350 Citations

MEGAHIT: An ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph

Dinghua Li;Chi-Man Liu;Ruibang Luo;Kunihiko Sadakane.
Bioinformatics (2015)

1674 Citations

The sequence and de novo assembly of the giant panda genome

Ruiqiang Li;Wei Fan;Geng Tian;Hongmei Zhu.
Nature (2010)

1166 Citations

SOAPdenovo-Trans: de novo transcriptome assembly with short RNA-Seq reads

Yinlong Xie;Yinlong Xie;Gengxiong Wu;Jingbo Tang;Ruibang Luo.
Bioinformatics (2014)

743 Citations

Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species

Keith R. Bradnam;Joseph N. Fass;Anton Alexandrov;Paul Baranay.
arXiv: Genomics (2013)

670 Citations

Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species

Keith R. Bradnam;Joseph N. Fass;Anton Alexandrov;Paul Baranay.
GigaScience (2013)

665 Citations

MEGAHIT v1.0: A fast and scalable metagenome assembler driven by advanced methodologies and community practices

Dinghua Li;Ruibang Luo;Chi-Man Liu;Chi-Ming Leung.
Methods (2016)

457 Citations

SOAP3-dp: Fast, Accurate and Sensitive GPU-based Short Read Aligner

Ruibang Luo;Thomas Kf Wong;Jianqiao Zhu;Jianqiao Zhu;Chi-Man Liu.
PLOS ONE (2013)

365 Citations

SOAP3: ultra-fast GPU-based parallel alignment tool for short reads.

Chi-Man Liu;Thomas K. F. Wong;Edward Wu;Ruibang Luo.
Bioinformatics (2012)

303 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.

If you think any of the details on this page are incorrect, let us know.

Contact us

Top Scientists Citing Tak-Wah Lam

Xun Xu

Xun Xu

Beijing Genomics Institute

Publications: 84

Guojie Zhang

Guojie Zhang

University of Copenhagen

Publications: 80

Xin Liu

Xin Liu

Chinese Academy of Sciences

Publications: 63

Didier Raoult

Didier Raoult

Aix-Marseille University

Publications: 58

Gonzalo Navarro

Gonzalo Navarro

University of Chile

Publications: 42

Steven L. Salzberg

Steven L. Salzberg

Johns Hopkins University

Publications: 42

Zhangjun Fei

Zhangjun Fei

Cornell University

Publications: 40

Patrick Wincker

Patrick Wincker

University of Paris-Saclay

Publications: 40

Wen Wang

Wen Wang

Northwestern Polytechnical University

Publications: 39

David Edwards

David Edwards

University of Western Australia

Publications: 38

Michael C. Schatz

Michael C. Schatz

Johns Hopkins University

Publications: 37

Wing-Kin Sung

Wing-Kin Sung

National University of Singapore

Publications: 35

Rajeev K. Varshney

Rajeev K. Varshney

International Crops Research Institute for the Semi-Arid Tropics

Publications: 35

Xiuqing Zhang

Xiuqing Zhang

Chinese Academy of Sciences

Publications: 35

Karsten Kristiansen

Karsten Kristiansen

University of Copenhagen

Publications: 33

Something went wrong. Please try again later.