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Haiming Tang

dblp:00/4016 · DBLP profile ↗
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4ranked-venue papers
3as first author
1since 2021 · last 2022
0000-0001-7058-349XORCID · corroborated

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

Applied, interdisciplinary, general and emerging computing · 3 · 2 first-author · 1 since 2021Software engineering, systems software and programming languages · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

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.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › protein function prediction
gene ontology annotation
0.412019
TreeGrafter: phylogenetic tree-based annotation of proteins with Gene Ontology terms and other annotations · Bioinform. 2019
Bioinformatics and computational biology › protein analysis › protein bioinformatics
protein annotation
0.412019
TreeGrafter: phylogenetic tree-based annotation of proteins with Gene Ontology terms and other annotations · Bioinform. 2019
Bioinformatics and computational biology › molecular evolution
protein evolution
0.212016
PANTHER-PSEP: predicting disease-causing genetic variants using position-specific evolutionary preservation · Bioinform. 2016
Bioinformatics and computational biology › statistical genetics › variant effect prediction
variant pathogenicity prediction
0.212016
PANTHER-PSEP: predicting disease-causing genetic variants using position-specific evolutionary preservation · Bioinform. 2016
Bioinformatics and computational biology › protein function prediction › sequence-based protein function prediction
homology-based function transfer
0.112019
TreeGrafter: phylogenetic tree-based annotation of proteins with Gene Ontology terms and other annotations · Bioinform. 2019

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

phylogenetic tree grafting · 0.4hidden markov model · 0.4phylogenetic ancestral sequence reconstruction · 0.2
YearPublicationVenuePosition
2022 Region Proposal Rectification Towards Robust Instance Segmentation of Biological Images
Qilong Zhangli, Jingru Yi, Di Liu 0003, Xiaoxiao He, Zhaoyang Xia, Ligong Han, Yunhe Gao, Song Wen 0001, Haiming Tang, He Wang 0016, Mu Zhou, Dimitris N. Metaxas
MICCAI (4)10
2019 TreeGrafter: phylogenetic tree-based annotation of proteins with Gene Ontology terms and other annotations
abstract
Summary: TreeGrafter is a new software tool for annotating protein sequences using pre-annotated phylogenetic trees. Currently, the tool provides annotations to Gene Ontology (GO) terms, and PANTHER family and subfamily. The approach is generalizable to any annotations that have been made to internal nodes of a reference phylogenetic tree. TreeGrafter takes each input query protein sequence, finds the best matching homologous family in a library of pre-calculated, pre-annotated gene trees, and then grafts it to the best location in the tree. It then annotates the sequence by propagating annotations from ancestral nodes in the reference tree. We show that TreeGrafter outperforms subfamily HMM scoring for correctly assigning subfamily membership, and that it produces highly specific annotations of GO terms based on annotated reference phylogenetic trees. This method will be further integrated into InterProScan, enabling an even broader user community. Availability and implementation: TreeGrafter is freely available on the web at https://github.com/pantherdb/TreeGrafter, including as a Docker image. Supplementary information: Supplementary data are available at Bioinformatics online.
Haiming Tang, Robert D. Finn, Paul D. Thomas
Bioinform.1
2016 PANTHER-PSEP: predicting disease-causing genetic variants using position-specific evolutionary preservation
abstract
UNLABELLED: PANTHER-PSEP is a new software tool for predicting non-synonymous genetic variants that may play a causal role in human disease. Several previous variant pathogenicity prediction methods have been proposed that quantify evolutionary conservation among homologous proteins from different organisms. PANTHER-PSEP employs a related but distinct metric based on 'evolutionary preservation': homologous proteins are used to reconstruct the likely sequences of ancestral proteins at nodes in a phylogenetic tree, and the history of each amino acid can be traced back in time from its current state to estimate how long that state has been preserved in its ancestors. Here, we describe the PSEP tool, and assess its performance on standard benchmarks for distinguishing disease-associated from neutral variation in humans. On these benchmarks, PSEP outperforms not only previous tools that utilize evolutionary conservation, but also several highly used tools that include multiple other sources of information as well. For predicting pathogenic human variants, the trace back of course starts with a human 'reference' protein sequence, but the PSEP tool can also be applied to predicting deleterious or pathogenic variants in reference proteins from any of the ∼100 other species in the PANTHER database. AVAILABILITY AND IMPLEMENTATION: PANTHER-PSEP is freely available on the web at http://pantherdb.org/tools/csnpScoreForm.jsp Users can also download the command-line based tool at ftp://ftp.pantherdb.org/cSNP_analysis/PSEP/ CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Haiming Tang, Paul D. Thomas
Bioinform.1
2008 A Tree-Based Method of Web Service Composition
abstract
Although service composition has received a great deal of attention and there are many solutions to the problem of composition, finding potential service compositions efficiently is still challenging because of the fact that the number of candidate services can be very large. In this paper, a tree-based method of Web service composition is proposed, by which all potential candidate composite services that meet the user's request can be created. Moreover, these composite services are ordered according to the QoS attribute concerned by the user, so the user can find the best and arbitrary top-n composite services.
Haiming Tang, Farong Zhong
ICWS1