Integrative Approaches of Artificial Intelligence and Multi-Omics in Cancer

AI-based multi-omics research has brought lots of outcomes and improvements in biological science, especially in cancer research and clinics. However, these cutting-edge techniques are inevitably facing lots of challenges. To clearly illustrate the advances and challenges in this interdisciplinary field, an updated overview of AI and multi-omics applications in cancer studies and an exploration of current paradigms of AI & omics in cancer research are lacking. Here we explore this question in three different aspects: application field, algorithms, and application paradigms of AI and multi-omics for cancer. This research brings out a high-resolution, well-structured landscape of AI and omics for cancer by summarizing reviews and recent related papers, and finally indicates the future direction of AI-powered multi-omics cancer study and research gaps that need to be explored.

Authors

Institutions

Publication Details

Journal
Theoretical and Natural Science
Published
2025-08-13
DOI
https://doi.org/10.54254/2753-8818/2025.au25982
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrative Approaches of Artificial Intelligence and Multi-Omics in Cancer

H Zhang
Theoretical and Natural Science
Bioinformatics and Genomic Networks
article

Integrative Approaches of Artificial Intelligence and Multi-Omics in Cancer

H Zhang
article en

Abstract

AI-based multi-omics research has brought lots of outcomes and improvements in biological science, especially in cancer research and clinics. However, these cutting-edge techniques are inevitably facing lots of challenges. To clearly illustrate the advances and challenges in this interdisciplinary field, an updated overview of AI and multi-omics applications in cancer studies and an exploration of current paradigms of AI & omics in cancer research are lacking. Here we explore this question in three different aspects: application field, algorithms, and application paradigms of AI and multi-omics for cancer. This research brings out a high-resolution, well-structured landscape of AI and omics for cancer by summarizing reviews and recent related papers, and finally indicates the future direction of AI-powered multi-omics cancer study and research gaps that need to be explored.

Theoretical and Natural ScienceVol. 124(1)
George Washington University (US)
Openalex Percentile: Top 82%
Bioinformatics and Genomic Networks
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Integrative Approaches of Artificial Intelligence and Multi-Omics in Cancer — H Zhang · Theoretical and Natural Science (2025) | TGRS Research Map | TGRS