<?xml version="1.0" encoding="UTF-8"?>
<records>
<record>
<language>eng</language>
<publisher>International Academy of Ecology and Environmental Sciences</publisher>
<journalTitle>Network Biology</journalTitle>
<eissn>2220-8879</eissn>
<publicationDate>2026-6-1</publicationDate>
<volume>16</volume>
<issue>2</issue>
<startPage>49</startPage>
<endPage>81</endPage>
<doi> </doi>
<publisherRecordId>2</publisherRecordId>
<documentType>article</documentType>
<title language="eng">TraitGenePathAna: The AI-Powered biological trait analysis platform</title>
<authors>
<author>
<name>WenJun Zhang</name>
<email></email>
<affiliationId>1</affiliationId>
<affiliationId>2</affiliationId>
</author>
</authors>
<affiliationsList>
<affiliationName affiliationId="1">
School of Life Sciences, Sun Yat-sen University, Guangzhou, China
</affiliationName>
</affiliationsList>
<abstract>
The AI-Powered biological trait analysis platform, TraitGenePathAna, is a single-page web application that helps a user explore the biology behind a trait (e.g., longevity, disease resistance) for a chosen species (e.g., Homo sapiens, Drosophila melanogaster). It does this by sending a structured prompt to an LLM provider (DeepSeek or Google Gemini, etc.) and then presenting the model's response in a multi-tab results UI: (1) Overview: summary, significance, broad context; (2) Genetics: key genes, loci, heritability and gene-level discussion; (3) Pathways: molecular mechanisms, signaling cascades, network view; (4) Interventions: potential strategies and caveats (research, ethics, feasibility). In addition, the platform can conduct inferences on hidden rules, patterns, and relationships.
</abstract>
<fullTextUrl format="pdf">
http://www.iaees.org/publications/journals/nb/articles/2026-16(2)/TraitGenePathAna.pdf
</fullTextUrl>
<keywords>
<keyword>Artificial Intelligence (AI)</keyword>
<keyword>biological trait</keyword>
<keyword>genes, pathways</keyword>
<keyword>web-based tool</keyword>
</keywords>
</record>
</records>
