Tootfinder

FAPS: A Fast Platform for Protein Structureomics Analysis
Lucas Wilken, Nihjum Paul, Troy Timmerman, Sara A. Tolba, Amara Arshad, Di Wu, Wenjie Xia, Bakhtiyor Rasulev, Rick Jansen, Dali Sun
https://arxiv.org/abs/2506.10134

FAPS: A Fast Platform for Protein Structureomics Analysis
Protein quantification and analysis are well-accepted approaches for biomarker discovery but are limited to identification without structural information. High-throughput omics data (i.e., genomics, transcriptomics, and proteomics) have become pervasive in cancer biology studies and reach well beyond more specialized areas such as metabolomics, epigenomics, pharmacogenomics, and interact-omics. However, large-scale analysis based on the structure of the biomolecules, namely structure-omics, is …

A nonparametric statistical method for deconvolving densities in the analysis of proteomic data
Akin Anarat, Jean Krutmann, Holger Schwender
https://arxiv.org/abs/2506.01540

A nonparametric statistical method for deconvolving densities in the analysis of proteomic data
In medical research, often, genomic or proteomic data are collected, with measurements frequently subject to uncertainties or errors, making it crucial to accurately separate the signals of the genes or proteins, respectively, from the noise. Such a signal separation is also of interest in skin aging research in which intrinsic aging driven by genetic factors and extrinsic, i.e.\ environmentally induced, aging are investigated by considering, e.g., the proteome of skin fibroblasts. Since extrin…

Refining Platelet Purification Methods: Enhancing Proteomics for Clinical Applications
Vibecke Markhus, Katarina Fritz-Wallace, Olav Mjaavatten, Einar K. Kristoffersen, Dorota Goplen, Frode Selheim
https://arxiv.org/abs/2505.24394

Refining Platelet Purification Methods: Enhancing Proteomics for Clinical Applications
Background: Platelet proteomics offers valuable insights for clinical research, yet isolating high-purity platelets remains a challenge. Current methods often lead to contamination or platelet loss, compromising data quality and reproducibility. Objectives: This study aimed to optimize a platelet isolation technique that yields high-purity samples with minimal loss and to identify the most effective mass spectrometry-based proteomic method for analyzing platelet proteins with optimal coverage…

Into the Unknown: From Structure to Disorder in Protein Function Prediction
{\DJ}esika Kolari\'c, Chi Fung Willis Chow, Rita Zi Zhu, Agnes Toth-Petroczy, T. Reid Alderson, Iva Priti\v{s}anac
https://arxiv.org/abs/2506.06004

Into the Unknown: From Structure to Disorder in Protein Function Prediction
Intrinsically disordered regions (IDRs) account for one-third of the human proteome and play essential biological roles. However, predicting the functions of IDRs remains a major challenge due to their lack of stable structures, rapid sequence evolution, and context-dependent behavior. Many predictors of protein function neglect or underperform on IDRs. Recent advances in computational biology and machine learning, including protein language models, alignment-free approaches, and IDR-specific m…

A coupled multiscale model of the human cornea accounting for the collagenous microstructure and the extracellular matrix
Christopher Miller, Maria Laura De Bellis, Anna Pandolfi
https://arxiv.org/abs/2507.00668

A coupled multiscale model of the human cornea accounting for the collagenous microstructure and the extracellular matrix
We present a micro-structurally based finite element model of the human cornea, where we explicitly describe the collagen-crosslink architecture in terms of a trusswork of non-linear struts, and the extracellular proteoglycan matrix in terms of continuum solid elements. We regard the cornea as a composite material with strongly non-linear properties within a finite kinematics framework. This innovative approach is based on two previously developed models, each of which has some drawbacks in des…

Active Gaussian Network Model: a non-equilibrium description of protein fluctuations and allosteric behavior
Giulio Costantini, Lorenzo Caprini, Umberto Marini Bettolo Marconi, Fabio Cecconi
https://arxiv.org/abs/2505.24855

Active Gaussian Network Model: a non-equilibrium description of protein fluctuations and allosteric behavior
Understanding the link between structure and function in proteins is fundamental in molecular biology and proteomics. A central question in this context is whether allostery - where the binding of a molecule at one site affects the activity of a distant site - emerges as a further manifestation of the intricate interplay between structure, function, and intrinsic dynamics. This study explores how allosteric regulation is modified when intrinsic protein dynamics operate under out-of-equilibrium …

Single-Cell Proteomic Technologies: Tools in the quest for principles
Nikolai Slavov
https://arxiv.org/abs/2506.18198 https://arxiv.o…

Single-Cell Proteomic Technologies: Tools in the quest for principles
Over the last decade, proteomic analysis of single cells by mass spectrometry transitioned from an uncertain possibility to a set of robust and rapidly advancing technologies supporting the accurate quantification of thousands of proteins. We review the major drivers of this progress, from establishing feasibility to powerful and increasingly scalable methods. We focus on the tradeoffs and synergies of different technological solutions within a coherent conceptual framework, which projects cons…

Beyond Olfaction: New Insights into Human Odorant Binding Proteins
Mifen Chen, Soufyan Lakbir, Mihyeon Jeon, Vojta Mazur, Sanne Abeln, Halima Mouhib
https://arxiv.org/abs/2507.03794

Beyond Olfaction: New Insights into Human Odorant Binding Proteins
Until today, the exact function of mammalian odorant binding proteins (OBPs) remains a topic of debate. Although their main established function lacks direct evidence in human olfaction, OBPs are traditionally believed to act as odorant transporters in the olfactory sense, which led to the exploration of OBPs as biomimetic sensor units in artificial noses. Now, available RNA-seq and proteomics data identified the expression of human OBPs (hOBP2A and hOBP2B) in both, male and female reproductive…

HEIST: A Graph Foundation Model for Spatial Transcriptomics and Proteomics Data
Hiren Madhu, Jo\~ao Felipe Rocha, Tinglin Huang, Siddharth Viswanath, Smita Krishnaswamy, Rex Ying
https://arxiv.org/abs/2506.11152

HEIST: A Graph Foundation Model for Spatial Transcriptomics and Proteomics Data
Single-cell transcriptomics has become a great source for data-driven insights into biology, enabling the use of advanced deep learning methods to understand cellular heterogeneity and transcriptional regulation at the single-cell level. With the advent of spatial transcriptomics data we have the promise of learning about cells within a tissue context as it provides both spatial coordinates and transcriptomic readouts. However, existing models either ignore spatial resolution or the gene regula…

Curriculum Learning for Biological Sequence Prediction: The Case of De Novo Peptide Sequencing
Xiang Zhang, Jiaqi Wei, Zijie Qiu, Sheng Xu, Nanqing Dong, Zhiqiang Gao, Siqi Sun
https://arxiv.org/abs/2506.13485

Curriculum Learning for Biological Sequence Prediction: The Case of De Novo Peptide Sequencing
Peptide sequencing-the process of identifying amino acid sequences from mass spectrometry data-is a fundamental task in proteomics. Non-Autoregressive Transformers (NATs) have proven highly effective for this task, outperforming traditional methods. Unlike autoregressive models, which generate tokens sequentially, NATs predict all positions simultaneously, leveraging bidirectional context through unmasked self-attention. However, existing NAT approaches often rely on Connectionist Temporal Clas…