English
Related papers

Related papers: Test-Time Tuned Language Models Enable End-to-end …

200 papers

The discovery and identification of molecules in biological and environmental samples is crucial for advancing biomedical and chemical sciences. Tandem mass spectrometry (MS/MS) is the leading technique for high-throughput elucidation of…

Nanobodies are small antibody fragments derived from camelids that selectively bind to antigens. These proteins have marked physicochemical properties that support advanced therapeutics, including treatments for SARS-CoV-2. To realize their…

Quantitative Methods · Quantitative Biology 2021-10-18 Chris McKennan , Zhe Sang , Yi Shi

Tandem mass spectrometry has played a pivotal role in advancing proteomics, enabling the high-throughput analysis of protein composition in biological tissues. Many deep learning methods have been developed for \emph{de novo} peptide…

Quantitative Methods · Quantitative Biology 2024-11-01 Jingbo Zhou , Shaorong Chen , Jun Xia , Sizhe Liu , Tianze Ling , Wenjie Du , Yue Liu , Jianwei Yin , Stan Z. Li

Tandem mass spectra capture fragmentation patterns that provide key structural information about a molecule. Although mass spectrometry is applied in many areas, the vast majority of small molecules lack experimental reference spectra. For…

Machine Learning · Computer Science 2023-05-03 Adamo Young , Bo Wang , Hannes Röst

Tandem mass spectrometry provides a high-throughput framework for identifying and quantifying proteins in complex biological samples. In computational proteomics, predicting peptide MS/MS spectra is a critical task, enabling downstream…

Machine Learning · Computer Science 2026-05-05 Zhiwen Yang , Pan Liu , Yifan Li , Yunhua Zhong , Jun Xia

Tandem mass spectrometry has played a pivotal role in advancing proteomics, enabling the analysis of protein composition in biological samples. Despite the development of various deep learning methods for identifying amino acid sequences…

Quantitative Methods · Quantitative Biology 2024-03-18 Jun Xia , Shaorong Chen , Jingbo Zhou , Tianze Ling , Wenjie Du , Sizhe Liu , Stan Z. Li

Liquid chromatography mass spectrometry (LC-MS)-based metabolomics and exposomics aim to measure detectable small molecules in biological samples. The results facilitate hypothesis-generating discovery of metabolic changes and disease…

Quantitative Methods · Quantitative Biology 2026-01-06 Xujun Che , Xiuxia Du , Depeng Xu

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 modified proteome. Standard database search algorithms suffer from…

Quantitative Methods · Quantitative Biology 2025-12-16 Yuhan Chen , Shang Qu , Zhiqiang Gao , Yuejin Yang , Xiang Zhang , Sheng Xu , Xinjie Mao , Liujia Qian , Jiaqi Wei , Zijie Qiu , Chenyu You , Lei Bai , Ning Ding , Tiannan Guo , Bowen Zhou , Siqi Sun

Mass spectrometry is the dominant technology in the field of proteomics, enabling high-throughput analysis of the protein content of complex biological samples. Due to the complexity of the instrumentation and resulting data, sophisticated…

Mass spectrometry (MS) stands as a cornerstone analytical technique for molecular identification, yet de novo structure elucidation from spectra remains challenging due to the combinatorial complexity of chemical space and the inherent…

Machine Learning · Computer Science 2026-03-20 Jianan Nie , Peng Gao

Molecular structure generation from mass spectrometry is fundamental for understanding cellular metabolism and discovering novel compounds. Although tandem mass spectrometry (MS/MS) enables the high-throughput acquisition of fragment…

Machine Learning · Computer Science 2026-02-03 Xichen Sun , Wentao Wei , Jiahua Rao , Jiancong Xie , Yuedong Yang

Machine learning methods for identifying molecular structures from tandem mass spectra (MS/MS) have advanced rapidly, yet current approaches still exhibit significant error rates. In high-stakes applications such as clinical metabolomics…

Machine Learning · Computer Science 2026-03-12 Mira Jürgens , Gaetan De Waele , Morteza Rakhshaninejad , Willem Waegeman

Automated molecular structure elucidation remains challenging, as existing approaches often depend on pre-compiled databases or restrict themselves to single spectroscopic modalities. Here we introduce SpectraLLM, a large language model…

Quantitative Methods · Quantitative Biology 2026-05-12 Yunyue Su , Jiahui Chen , Zao Jiang , Zhenyi Zhong , Liang Wang , Qiang Liu , Zhaoxiang Zhang

Tandem mass spectrometry (MS/MS) is a high-throughput technology used toidentify the proteins in a complex biological sample, such as a drop of blood. A collection of spectra is generated at the output of the process, each spectrum of which…

Quantitative Methods · Quantitative Biology 2019-09-06 John T. Halloran , David M. Rocke

Peptide identification in mass spectrometry-based proteomics is crucial for understanding protein function and dynamics. Traditional database search methods, though widely used, rely on heuristic scoring functions and statistical…

Quantitative Methods · Quantitative Biology 2024-05-13 Yonghan Yu , Ming Li

De novo peptide sequencing algorithms have been widely used in proteomics to analyse tandem mass spectra (MS/MS) and assign them to peptides, but quality-control methods to evaluate the confidence of de novo peptide sequencing are lagging…

Neural and Evolutionary Computing · Computer Science 2019-08-22 Samaneh Azari , Bing Xue , Mengjie Zhang , Lifeng Peng

Proteomics is the large-scale analysis of the proteins. The common method for identifying proteins and characterising their amino acid sequences is to digest the proteins into peptides, analyse the peptides using mass spectrometry and…

Computational Engineering, Finance, and Science · Computer Science 2019-02-05 Samaneh Azari , Bing Xue , Mengjie Zhang , Lifeng Peng

Molecular dynamics (MD) is a central computational tool in physics, chemistry, and biology, enabling quantitative prediction of experimental observables as expectations over high-dimensional molecular distributions such as Boltzmann…

Machine Learning · Computer Science 2026-02-13 Panagiotis Antoniadis , Beatrice Pavesi , Simon Olsson , Ole Winther

The identification and property prediction of chemical molecules is of central importance in the advancement of drug discovery and material science, where the tandem mass spectrometry technology gives valuable fragmentation cues in the form…

Artificial Intelligence · Computer Science 2026-04-14 Yunhua Zhong , Yixuan Tang , Yifan Li , Jie Yang , Pan Liu , Jun Xia

Small-molecule identification from tandem mass spectrometry (MS/MS) remains a bottleneck in untargeted settings where spectral libraries are incomplete. While deep learning offers a solution, current approaches typically fall into two…

Machine Learning · Computer Science 2026-03-05 Yinkai Wang , Yan Zhou Chen , Xiaohui Chen , Li-Ping Liu , Soha Hassoun
‹ Prev 1 2 3 10 Next ›