MEMOL: Mixture of experts for multimodal learning through multi-head attention to predict drug toxicity

MEMOL demonstrates superior performance in toxicity prediction, achieving consistent improvements across diverse datasets and offering a robust framework for integrating molecular representations.

Authors

Young‐Rae Cho (ORCID: https://orcid.org/0000-0002-4645-2542)
Jae-Woo Chu (ORCID: https://orcid.org/0009-0002-8193-5600)
Jong-Hoon Park (ORCID: https://orcid.org/0000-0002-8774-5640)

Institutions

Yonsei University (KR)

Publication Details

Journal: Computer Methods and Programs in Biomedicine
Published: 2025-09-30
DOI: https://doi.org/10.1016/j.cmpb.2025.109088
Citations: 2
Primary Topic: Computational Drug Discovery Methods
Type: article
Field-Weighted Citation Impact: 3.01

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

MEMOL: Mixture of experts for multimodal learning through multi-head attention to predict drug toxicity

Young‐Rae Cho, Jae-Woo Chu, Jong-Hoon Park

Sep 30, 2025

2 citations

Computer Methods and Programs in Biomedicine

Computational Drug Discovery Methods

3.01

article

MEMOL: Mixture of experts for multimodal learning through multi-head attention to predict drug toxicity

Young‐Rae Cho, Jae-Woo Chu, Jong-Hoon Park

September 30, 2025article en

2 citations

Abstract

MEMOL demonstrates superior performance in toxicity prediction, achieving consistent improvements across diverse datasets and offering a robust framework for integrating molecular representations.

Computer Methods and Programs in BiomedicineVol. 273

Yonsei University (KR)

Openalex Percentile: Top 7%

Computational Drug Discovery Methods

3.01

DOI Open Access PDF OpenAlex

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.

MEMOL: Mixture of experts for multimodal learning through multi-head attention to predict drug toxicity — Young‐Rae Cho, Jae-Woo Chu, et al. · Computer Methods and Programs in Biomedicine (2025) | TGRS Research Map | TGRS