ERAM aligns pre-trained molecular representations from Protein Language Model with the knowledge of enzyme catalysis by modeling enzymatic reactions as multi-relational data, and demonstrates its potential as a versatile and effective tool for enzyme catalysis research.
This study introduces LaMGen, an LLM-powered framework that leverages large-scale protein-ligand data and rotation-aware molecular encoding to rapidly produce chemically plausible multi-target candidates, achieving strong zero-shot generalization, superior molecular quality, and robust performance across dual- and trip...
Qun Su, Qiaolin Gou, Hui Zhang et al.· Nature Communications· 1 citation
The Biotoxins Database (BioTD) is the largest open-source database for toxins, offering open access to 14,607 data records (8,185 activity records), covering 8,975 toxins sourced from 5,220 references and patents across over 900 species.
Gaoang Wang, Hang Wu, Yang Liao et al.· Journal of Chemical Informat...· 0 citations
BBBP-Atlas is proposed, a structure-aware BBB permeability prediction model designed for unified modeling of small molecules and peptides with the first cross-modal dataset OmniBBBP, which offers a versatile and cross-modal approach for single-compound prediction, batch screening, and dataset exploration for CNS drug d...
Xin Shen, Qun Su, Hao Luo et al.· bioRxiv· 0 citations
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While LLM-based multi-agent systems show potential for large-scale software development, successful integration requires addressing challenges such as memory limitations, hallucinations, and code smells, alongside a practitioner-centric perspective.
Z. Rasheed, Muhammad Waseem, Kai-Kristian Kemell et al.· 31 citations
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
This work designs and operationalizes a governance-aware, multi-tenant AI sandbox that supports structured experimentation and produces reusable evaluation evidence across stakeholders and yields lessons learned and practical considerations that inform deployment and future evolution of governance-aware sandbox platfor...
Muhammad Waseem, M. Islam, Md Nasir Uddin Shuvo et al.· arXiv.org· 1 citation
This work presents the design and implementation of a governance-aware, multi-tenant AI sandbox for structured experimentation and the generation of reusable evaluation evidence across projects and stakeholder groups.
Muhammad Waseem, M. Islam, Md Nasir Uddin Shuvo et al.· arXiv.org· 0 citations
A Multi-Vocal Literature Review is conducted, combining insights from both academia and industry, including peer-reviewed studies and grey literature to systematically synthesize and analyze existing knowledge on LLM-based multi-agent systems for code generation.
Z. Rasheed, Muhammad Waseem, Kai-Kristian Kemell et al.· arXiv.org· 2 citations
This study provides the first large-scale empirical comparison of agentic frameworks for reasoning-intensive software engineering tasks and shows that framework selection should prioritize orchestration quality, especially memory control, failure handling, and cost management.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 1 citation
The vision is to leverage the capabilities of multiple GPT agents to contribute to SE tasks and to propose an initial road map for future work, arguing that multiple G PT agents can perform creative and demanding tasks far beyond coding and debugging.
Z. Rasheed, Muhammad Waseem, Kai-Kristian Kemell et al.· XP Workshops· 34 citations· ⚡2
A machine-learning approach called CheMeleon provides a practical way to develop new drugs or other molecules with much less detailed, expensive experimentation.