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Alex Shiang

dblp:370/5902 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 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
1 paper
Bioinformatics and computational biology · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › cancer genomics
circulating tumor DNA analysis
0.712023
PACT: a pipeline for analysis of circulating tumor DNA · Bioinform. 2023
Bioinformatics and computational biology › genomics › structural variation
structural variant detection
0.712023
PACT: a pipeline for analysis of circulating tumor DNA · Bioinform. 2023
Distributed systems
workflow management
0.212023
PACT: a pipeline for analysis of circulating tumor DNA · Bioinform. 2023

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

common workflow language · 1.3
YearPublicationVenuePosition
2023 PACT: a pipeline for analysis of circulating tumor DNA
abstract
MOTIVATION: Detection of genomic alterations in circulating tumor DNA (ctDNA) is currently used for active clinical monitoring of cancer progression and treatment response. While methods for analysis of small mutations are more developed, strategies for detecting structural variants (SVs) in ctDNA are limited. Additionally, reproducibly calling small-scale mutations, copy number alterations, and SVs in ctDNA is challenging due to the lack to unified tools for these different classes of variants. RESULTS: We developed a unified pipeline for the analysis of ctDNA [Pipeline for the Analysis of ctDNA (PACT)] that accurately detects SVs and consistently outperformed similar tools when applied to simulated, cell line, and clinical data. We provide PACT in the form of a Common Workflow Language pipeline which can be run by popular workflow management systems in high-performance computing environments. AVAILABILITY AND IMPLEMENTATION: PACT is freely available at https://github.com/ChrisMaherLab/PACT.
Jace Webster, Ha X. Dang, Pradeep S. Chauhan, Wenjia Feng, Alex Shiang, Peter K. Harris, Russell K. Pachynski, Aadel A. Chaudhuri, Christopher A. Maher
Bioinform.5