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Michael Chapman

dblp:35/6352 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2019
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2Theory of computation · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Graph algorithms and graph theory · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Graph algorithms and graph theory
expander graphs
0.412019
Expander Graphs - Both Local and Global · FOCS 2019
Graph algorithms and graph theory
graph theory
0.412019
Expander Graphs - Both Local and Global · FOCS 2019
Bioinformatics and computational biology › gene regulation › gene regulatory network
gene regulatory network analysis
0.112005
TFBScluster: a resource for the characterization of transcriptional regulatory networks · Bioinform. 2005
Bioinformatics and computational biology › gene regulation › transcription factor binding site prediction
transcription factor binding site cluster identification
0.112005
TFBScluster: a resource for the characterization of transcriptional regulatory networks · Bioinform. 2005

Methods — techniques the papers use, named apart from their topics

comparative genomics · 0.1
YearPublicationVenuePosition
2019 Expander Graphs - Both Local and Global
Michael Chapman, Nathan Linial, Yuval Peled
FOCS1
2005 TFBScluster: a resource for the characterization of transcriptional regulatory networks
abstract
SUMMARY: One major challenge of the post-sequencing era of the human genome project will be the functional annotation of the non-coding portion of the genome, in particular gene regulatory sequences. We have developed a new web-based tool, TFBScluster, which performs genome-wide identification of transcription factor binding site clusters that are conserved in multiple mammalian genomes. Clusters representing candidate gene regulatory elements can be filtered further, based on the presence or absence of additional user-defined DNA sequence motifs or by constraining the orientation or order of binding sites. Comprehensive results files, returned by email, are designed to facilitate experimental validation of computationally identified candidate gene regulatory sequences. TFBScluster, therefore, has the potential to contribute to deciphering transcriptional networks that regulate a wide range of mammalian developmental processes.
Ian John Donaldson, Michael Chapman, Berthold Göttgens
Bioinform.2
2003 Fast and sensitive multiple alignment of large genomic sequences
abstract
BACKGROUND: Genomic sequence alignment is a powerful method for genome analysis and annotation, as alignments are routinely used to identify functional sites such as genes or regulatory elements. With a growing number of partially or completely sequenced genomes, multiple alignment is playing an increasingly important role in these studies. In recent years, various tools for pair-wise and multiple genomic alignment have been proposed. Some of them are extremely fast, but often efficiency is achieved at the expense of sensitivity. One way of combining speed and sensitivity is to use an anchored-alignment approach. In a first step, a fast search program identifies a chain of strong local sequence similarities. In a second step, regions between these anchor points are aligned using a slower but more accurate method. RESULTS: Herein, we present CHAOS, a novel algorithm for rapid identification of chains of local pair-wise sequence similarities. Local alignments calculated by CHAOS are used as anchor points to improve the running time of DIALIGN, a slow but sensitive multiple-alignment tool. We show that this way, the running time of DIALIGN can be reduced by more than 95% for BAC-sized and longer sequences, without affecting the quality of the resulting alignments. We apply our approach to a set of five genomic sequences around the stem-cell-leukemia (SCL) gene and demonstrate that exons and small regulatory elements can be identified by our multiple-alignment procedure. CONCLUSION: We conclude that the novel CHAOS local alignment tool is an effective way to significantly speed up global alignment tools such as DIALIGN without reducing the alignment quality. We likewise demonstrate that the DIALIGN/CHAOS combination is able to accurately align short regulatory sequences in distant orthologues.
Michael Brudno, Michael Chapman, Berthold Göttgens, Serafim Batzoglou, Burkhard Morgenstern
BMC Bioinform.2