7 citations · 17 across the 10 of their papers we have counts for
6 papers · 1 filter
Evaluating Large Language Models in Scientific Discovery
Zhangde Song, Jieyu Lu, Yuanqi Du +53
Large language models (LLMs) are increasingly applied to scientific research, yet prevailing science benchmarks probe decontextualized knowledge and overlook the iterative reasonin…
General Intelligence-based Fragmentation (GIF): A framework for peak-labeled spectra simulation
Margaret R. Martin, Soha Hassoun
Despite growing reference libraries and advanced computational tools, progress in the field of metabolomics remains constrained by low rates of annotating measured spectra. The rec…
MetaboT: An LLM-based Multi-Agent Frameworkfor Interactive Analysis of Mass SpectrometryMetabolomics Knowledge Graphs
Madina Bekbergenova, Lucas Pradi, Benjamin Navet +15
Mass spectrometry-based metabolomics generates complex, high-dimensional data that holds vast potential for biological discovery but remains difficult to integrate and interpret. K…
Large Language Model is Secretly a Protein Sequence Optimizer
Yinkai Wang, Jiaxing He, Yuanqi Du +5
We consider the protein sequence engineering problem, which aims to find protein sequences with high fitness levels, starting from a given wild-type sequence. Directed evolution ha…
MADGEN: Mass-Spec attends to De Novo Molecular generation
Yinkai Wang, Xiaohui Chen, Liping Liu +1
The annotation (assigning structural chemical identities) of MS/MS spectra remains a significant challenge due to the enormous molecular diversity in biological samples and the lim…
Graph Generative Pre-trained Transformer
Xiaohui Chen, Yinkai Wang, Jiaxing He +4
Graph generation is a critical task in numerous domains, including molecular design and social network analysis, due to its ability to model complex relationships and structured da…