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Kuei-Yueh Ko

dblp:311/3076 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2022
0000-0001-8564-8524ORCID · reported

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

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 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%

Topics — the 1 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › network bioinformatics › biological network analysis
network analysis
0.612022
Phylotranscriptomic patterns of network stochasticity and pathway dynamics during embryogenesis · Bioinform. 2022

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

stochastic network analysis · 0.6gene-set pathway analysis · 0.6
YearPublicationVenuePosition
2022 Phylotranscriptomic patterns of network stochasticity and pathway dynamics during embryogenesis
abstract
MOTIVATION: The hourglass model is a popular evo-devo model depicting that the developmental constraints in the middle of a developmental process are higher, and hence the phenotypes are evolutionarily more conserved, than those that occur in early and late ontogeny stages. Although this model has been supported by studies analyzing developmental gene expression data, the evolutionary explanation and molecular mechanism behind this phenomenon are not fully understood yet. To approach this problem, Raff proposed a hypothesis and claimed that higher interconnectivity among elements in an organism during organogenesis resulted in the larger constraints at the mid-developmental stage. By employing stochastic network analysis and gene-set pathway analysis, we aim to demonstrate such changes of interconnectivity claimed in Raff's hypothesis. RESULTS: We first compared the changes of network randomness among developmental processes in different species by measuring the stochasticity within the biological network in each developmental stage. By tracking the network entropy along each developmental process, we found that the network stochasticity follows an anti-hourglass trajectory, and such a pattern supports Raff's hypothesis in dynamic changes of interconnections among biological modules during development. To understand which biological functions change during the transition of network stochasticity, we sketched out the pathway dynamics along the developmental stages and found that species may activate similar groups of biological processes across different stages. Moreover, higher interspecies correlations are found at the mid-developmental stages. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Kuei-Yueh Ko, Cho-Yi Chen, Hsueh-Fen Juan, Hsuan-Cheng Huang
Bioinform.1