8 citations · 16 across the 10 of their papers we have counts for
11 papers
ResearchClawBench: A Benchmark for End-to-End Autonomous Scientific Research
Wanghan Xu, Shuo Li, Tianlin Ye +48
AI coding agents are increasingly used for scientific work, but their end-to-end autonomous research capability remains difficult to verify. We present ResearchClawBench, a benchma…
Structure-guided taxonomic placement of divergent RNA viruses with ViraClass
Sheng Xu, Wenxuan Huang, Shutong Yue +8
Metatranscriptomic sequencing has expanded our knowledge of the RNA virosphere far more rapidly than novel viruses can be taxonomically classified. Taxonomic assignment above the f…
ViraHinter: a dual-modal artificial intelligence framework for predicting virus-host interactions
Weiqiang Bai, Fei Wang, Jialin Wang +10
Protein-protein interactions (PPIs) between a virus and its host govern infection, replication, and pathogenesis. While high-throughput mapping has identified thousands of virus-ho…
Accurate de novo sequencing of the modified proteome with OmniNovo
Yuhan Chen, Shang Qu, Zhiqiang Gao +13
Post-translational modifications (PTMs) serve as a dynamic chemical language regulating protein function, yet current proteomic methods remain blind to a vast portion of the modifi…
Bidirectional Representations Augmented Autoregressive Biological Sequence Generation
Xiang Zhang, Jiaqi Wei, Zijie Qiu +5
Autoregressive (AR) models, common in sequence generation, are limited in many biological tasks such as de novo peptide sequencing and protein modeling by their unidirectional natu…
Curriculum Learning for Biological Sequence Prediction: The Case of De Novo Peptide Sequencing
Xiang Zhang, Jiaqi Wei, Zijie Qiu +4
Peptide sequencing-the process of identifying amino acid sequences from mass spectrometry data-is a fundamental task in proteomics. Non-Autoregressive Transformers (NATs) have prov…
Scientists' First Exam: Probing Cognitive Abilities of MLLM via Perception, Understanding, and Reasoning
Yuhao Zhou, Yiheng Wang, Xuming He +26
Scientific discoveries increasingly rely on complex multimodal reasoning based on information-intensive scientific data and domain-specific expertise. Empowered by expert-level sci…
Universal Biological Sequence Reranking for Improved De Novo Peptide Sequencing
Zijie Qiu, Jiaqi Wei, Xiang Zhang +6
De novo peptide sequencing is a critical task in proteomics. However, the performance of current deep learning-based methods is limited by the inherent complexity of mass spectrome…
BEACON: Benchmark for Comprehensive RNA Tasks and Language Models
Yuchen Ren, Zhiyuan Chen, Lifeng Qiao +10
RNA plays a pivotal role in translating genetic instructions into functional outcomes, underscoring its importance in biological processes and disease mechanisms. Despite the emerg…
CrossBind: Collaborative Cross-Modal Identification of Protein Nucleic-Acid-Binding Residues
Linglin Jing, Sheng Xu, Yifan Wang +6
Accurate identification of protein nucleic-acid-binding residues poses a significant challenge with important implications for various biological processes and drug design. Many ty…
ContraNovo: A Contrastive Learning Approach to Enhance De Novo Peptide Sequencing
Zhi Jin, Sheng Xu, Xiang Zhang +6
De novo peptide sequencing from mass spectrometry (MS) data is a critical task in proteomics research. Traditional de novo algorithms have encountered a bottleneck in accuracy due…