Bioinformatics advances最新文献_第2页

BLITSFR: scalable comparative genomics with self-contained interactive single file report. BLITSFR：可扩展的比较基因组学与自包含的交互式单文件报告。

IF 2.6

Bioinformatics advances Pub Date : 2026-09-25 eCollection Date: 2026-01-01 DOI: 10.1093/bioadv/vbag282

Budi Permana, Thom Cuddihy, Brian M Forde

{"title":"BLITSFR: scalable comparative genomics with self-contained interactive single file report.","authors":"Budi Permana, Thom Cuddihy, Brian M Forde","doi":"10.1093/bioadv/vbag282","DOIUrl":"https://doi.org/10.1093/bioadv/vbag282","url":null,"abstract":"Motivation: Comparative genomics routinely requires the alignment of query genomes against a reference to delineate conserved and variable regions, yet existing tools often produce static visualisations or necessitate centralised web services and data uploads.Results: To address this, we present BLITSFR (BLAST Interactive Tracks in Single-File Report), a command-line tool that compares query genomes against a reference and returns a single interactive HTML file. The report opens in any modern browser, requiring no server or data upload, and lets users explore conserved and variable regions across the genomes. BLITSFR handles both assembled genomes and raw reads, and processes hundreds of genomes in minutes on a standard laptop with genome tracks sorting, filtering, and colouring by metadata are performed within the report, without requirement for re-running the analysis. We demonstrate its utility by analysing vancomycin-resistant Enterococcus faecium ST78 genomes to confirm the conservation of Tn1549-like transposons and a case of β-lactam-resistant Corynebacterium diphtheriae, where coverage depth resolved resistance transposon copy number.Availability and implementation: BLITSFR and SCIFR are freely available at the provided GitHub repositories (https://github.com/nalarbp/blitsfr, https://github.com/nalarbp/scifr).","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"6 1","pages":"vbag282"},"PeriodicalIF":2.6,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13657425/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149186576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DNA breathing and shape encode distinct mechanisms of transcription factor binding. DNA呼吸和形状编码不同的转录因子结合机制。

IF 2.6

Bioinformatics advances Pub Date : 2026-09-25 eCollection Date: 2026-01-01 DOI: 10.1093/bioadv/vbag287

Tsu-Pei Chiu, Wei Yu Tang, Waqaas Butt, Boqiao Lai, Sheng Qian, Boian S Alexandrov, Jubao Duan, Xin He, Remo Rohs

{"title":"DNA breathing and shape encode distinct mechanisms of transcription factor binding.","authors":"Tsu-Pei Chiu, Wei Yu Tang, Waqaas Butt, Boqiao Lai, Sheng Qian, Boian S Alexandrov, Jubao Duan, Xin He, Remo Rohs","doi":"10.1093/bioadv/vbag287","DOIUrl":"10.1093/bioadv/vbag287","url":null,"abstract":"Motivation: Interactions between transcription factors (TFs) and DNA play a key role in regulating gene expression. While these interactions are often viewed primarily as recognition of DNA sequence motifs, several studies have shown the limitation of this approach and highlighted the impact of physical properties of DNA. Prior studies have supported the importance of DNA shape features as determinant of TF-DNA recognition. Another physical property is DNA breathing, the spontaneous and transient opening of double-stranded DNA through thermal motions, which has not been systematically examined.Results: We analyzed in vitro TF-DNA binding data and found that DNA breathing features in motif regions are correlated with binding affinity, highlighting a role of locally and temporally melted DNA. Here, we compared contributions of DNA breathing and shape to TF binding. These analyses suggest that DNA breathing provides sequence-dependent information related to DNA structure not fully captured by DNA shape. Extending the analysis to ChIP-seq data, we found that breathing features are associated with TF binding in vivo, although the direction and magnitude of these associations vary across TFs. Our results support DNA breathing as an additional physical feature contributing to TF-DNA interactions alongside DNA sequence motifs and DNA shape.Availability and implementation: Data and analysis code are available at https://doi.org/10.17605/OSF.IO/UAHBJ and https://github.com/TsuPeiChiu/DNAbreathing.","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"6 1","pages":"vbag287"},"PeriodicalIF":2.6,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13665466/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149198221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RCSB PDB AI Help Desk: retrieval-augmented generation for protein structure deposition support. RCSB PDB AI帮助台：检索增强生成蛋白质结构沉积支持。

IF 2.6

Bioinformatics advances Pub Date : 2026-09-25 eCollection Date: 2026-01-01 DOI: 10.1093/bioadv/vbag289

Vivek Reddy Chithari, Jasmine Y Young, Irina Persikova, Yuhe Liang, Gregg V Crichlow, Justin W Flatt, Sutapa Ghosh, Brian P Hudson, Ezra Peisach, Monica Sekharan, Chenghua Shao, Stephen K Burley

{"title":"RCSB PDB AI Help Desk: retrieval-augmented generation for protein structure deposition support.","authors":"Vivek Reddy Chithari, Jasmine Y Young, Irina Persikova, Yuhe Liang, Gregg V Crichlow, Justin W Flatt, Sutapa Ghosh, Brian P Hudson, Ezra Peisach, Monica Sekharan, Chenghua Shao, Stephen K Burley","doi":"10.1093/bioadv/vbag289","DOIUrl":"https://doi.org/10.1093/bioadv/vbag289","url":null,"abstract":"Motivation: Structural biologists have contributed more than 260 000 experimentally determined three-dimensional structures of biological macromolecules to the Protein Data Bank. Incoming depositions are validated and biocurated by approximately 20 expert biocurators at the collaborating data centers worldwide. Biocurators at the Research Collaboratory for Structural Bioinformatics Protein Data Bank, who process more than 40% of global depositions, face growing difficulty sustaining efficient Help Desk operations, having received roughly 19 000 depositor messages across some 8000 entries in 2025.Results: We developed an artificial intelligence Help Desk assistant built on retrieval-augmented generation. Source documents are converted to Markdown with layout preserved, divided by a two-stage chunking procedure, embedded, and stored in a relational vector database. At query time, maximal marginal relevance retrieval selects diverse supporting passages, a topical guardrail filters out-of-scope questions, and a purpose-built system prompt prevents disclosure of internal curation terminology. Separate language model configurations handle question condensing and answer generation. The service runs in production on a container orchestration platform, providing around-the-clock depositor assistance with streaming, citation-backed responses.Availability and implementation: Freely available at https://rcsb-deposit-help.rcsb.org. Source code: https://github.com/rcsb/rcsb-pdb-helpdesk (archived at Zenodo: https://doi.org/10.5281/zenodo.19560785).","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"6 1","pages":"vbag289"},"PeriodicalIF":2.6,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13652142/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149167873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

FerroEnrich: an interactive web platform for liver-focused ferroptosis index scoring, enrichment, and ferroptosis-senescence cross-talk analysis. ferroenrichment：一个以肝脏为中心的铁下垂指数评分、富集和铁下垂-衰老交叉分析的交互式网络平台。

IF 2.6

Bioinformatics advances Pub Date : 2026-09-24 eCollection Date: 2026-01-01 DOI: 10.1093/bioadv/vbag285

Munichandra Babu Tirumalasetty, Mayank Choubey, Mohammad Sarif Mohiuddin, Rashu Barua, Wahiduzzaman Md, Qing Robert Miao

{"title":"FerroEnrich: an interactive web platform for liver-focused ferroptosis index scoring, enrichment, and ferroptosis-senescence cross-talk analysis.","authors":"Munichandra Babu Tirumalasetty, Mayank Choubey, Mohammad Sarif Mohiuddin, Rashu Barua, Wahiduzzaman Md, Qing Robert Miao","doi":"10.1093/bioadv/vbag285","DOIUrl":"https://doi.org/10.1093/bioadv/vbag285","url":null,"abstract":"Motivation: Ferroptosis is an iron-dependent regulated cell death process involving lipid peroxidation, redox imbalance, and impaired antioxidant defense. It is increasingly relevant to metabolic liver disease and non-alcoholic steatohepatitis. Existing ferroptosis resources mainly provide gene annotations and disease associations, but they do not offer an integrated workflow for user-uploaded transcriptome data, liver-focused enrichment, dataset-level scoring, and ferroptosis-senescence cross-talk analysis.Results: We developed FerroEnrich, an open-source web platform for analyzing ferroptosis and senescence programs in human and mouse liver transcriptome datasets. FerroEnrich supports count matrix upload, metadata-guided differential expression analysis, identification of ferroptosis-prone and ferroptosis-resistant genes, dataset-level ferroptosis index scoring, sample-level susceptibility estimation, curated liver module enrichment, interaction network visualization, and ferroptosis-senescence cross-talk analysis. Application to human advanced non-alcoholic steatohepatitis and mouse diet-induced liver disease datasets demonstrated cross-species utility and identified conserved remodeling, including reduced ferroptosis-protective signatures and increased senescence- and fibrosis-associated modules.Availability and implementation: FerroEnrich is freely available at https://ferroenrich.shinyapps.io/ferroenrich/. Source code, documentation, and demo datasets are available at the FerroEnrich GitHub repository.","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"6 1","pages":"vbag285"},"PeriodicalIF":2.6,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13652149/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149170388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

OOPSIE (OOPS informatics extension). OOPSIE （ops信息学扩展）。

IF 2.6

Bioinformatics advances Pub Date : 2026-09-23 eCollection Date: 2026-01-01 DOI: 10.1093/bioadv/vbag278

Stephanie B Telerman, Lajos Kalmar, Sandip K Patel, Anne E Willis, Kathryn S Lilley

{"title":"OOPSIE (OOPS informatics extension).","authors":"Stephanie B Telerman, Lajos Kalmar, Sandip K Patel, Anne E Willis, Kathryn S Lilley","doi":"10.1093/bioadv/vbag278","DOIUrl":"10.1093/bioadv/vbag278","url":null,"abstract":"Motivation: The RNA-bound proteome represents a dynamic and pleiotropic network of RNA-binding proteins (RBPs) that integrate diverse cellular pathways. RNA-binding dynamics profiling using cross-linking-based enrichment strategies including Orthogonal Organic Phase Separation (OOPS), generates complex peptide-level quantitative mass spectrometry datasets, yet dedicated computational workflows for standardized normalization and differential analysis remain limited.Results: OOPS relies on phase partitioning of RNA binding proteomes, upon UV cross-linking. As glycoproteins have been shown to co-partition independently of cross-linking due to their physicochemical properties, they provide a cross-link-independent reference population that can be leveraged for normalization of RNA-binding-dependent changes. We introduce OOPSIE (Orthogonal Organic Phase Separation Informatics Extension), an R-based script that provides a reproducible framework of peptide-level OOPS-derived data using protein-level normalization and differential analysis of RNA-binding capacity. We demonstrate its utility using OOPS-derived datasets generated from A549 lung adenocarcinoma cells.Availability and implementation: OOPSIE is implemented in R as a standalone workflow and is freely available at https://github.com/CambridgeCentreForProteomics/oopsie, together with documentation and example datasets.","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"6 1","pages":"vbag278"},"PeriodicalIF":2.6,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13671718/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149217285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Employing AlphaFold and TED to explore the structural impacts of stress-associated mutations in rice. 利用AlphaFold和TED来探索水稻中与胁迫相关的突变的结构影响。

IF 2.6

Bioinformatics advances Pub Date : 2026-09-22 eCollection Date: 2026-01-01 DOI: 10.1093/bioadv/vbag275

Fatima Shahid, Neeladri Sen, Christine Orengo, Su Datt Lam

{"title":"Employing AlphaFold and TED to explore the structural impacts of stress-associated mutations in rice.","authors":"Fatima Shahid, Neeladri Sen, Christine Orengo, Su Datt Lam","doi":"10.1093/bioadv/vbag275","DOIUrl":"https://doi.org/10.1093/bioadv/vbag275","url":null,"abstract":"Motivation: Plants have evolved adaptive mechanisms to handle environmental stress. However, genome-wide association studies (GWASs) have identified genetic variations associated with stress resistance, yet their structural and functional impacts remain poorly understood. This limits our ability to develop more resilient crops.Results: Using predicted three-dimensional protein structures from the AlphaFold Database, chopped into domains by The Encyclopedia of Domains, we analysed how mutations identified in rice GWASs affect protein structure and function. The analysis revealed 102 mutations in 76 high-quality protein domains likely to impact structure and function. Thirty-nine mutations were positioned within 5 Å of predicted functional sites, including those near post-translational modification sites (3), allosteric sites (5), protein-protein interaction sites (25), ligand-binding sites (15), and conserved regions (9). We identified potential interaction partners for 18 proteins with mutations at predicted interfaces and modelled their complex structures. Six mutations were predicted to enhance binding affinity with their protein partners.Availability and implementation: This study utilized only open-access tools and and provides a framework that could strengthen plant defence mechanisms. However, experimental validation is essential to confirm the applicability of these findings for plant breeding programs.","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"6 1","pages":"vbag275"},"PeriodicalIF":2.6,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13652148/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149171364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

pycmplot: fast, low-memory multi-track circular and linear Manhattan plotting in Python. pycmplot: Python中的快速，低内存多轨道圆形和线性曼哈顿绘图。

IF 2.6

Bioinformatics advances Pub Date : 2026-09-22 eCollection Date: 2026-01-01 DOI: 10.1093/bioadv/vbag281

Kevin Esoh, Fujr Osman, Cesar Fortes-Lima, Gordon A Awandare, Ambroise Wonkam

{"title":"pycmplot: fast, low-memory multi-track circular and linear Manhattan plotting in Python.","authors":"Kevin Esoh, Fujr Osman, Cesar Fortes-Lima, Gordon A Awandare, Ambroise Wonkam","doi":"10.1093/bioadv/vbag281","DOIUrl":"10.1093/bioadv/vbag281","url":null,"abstract":"Motivation: Manhattan plots remain the standard visual summary for genome-wide association studies and other per-variant scans (iHS, FST, XP-EHH). Existing Manhattan visualization tools either lack multi-track support (gwaslab, qmplot, and qqman) or do not provide a Circos-style multi-track circular Manhattan view. CMplot (R) does, but its memory and runtime costs on multi-million-variant inputs are substantial.Results: We present pycmplot, a Python package for generating multi-track linear and Circos-style circular Manhattan plots from one or more GWAS summary statistics. On a 10-million-variant scan, pycmplot is 5.5× faster and uses ∼5× less memory than CMplot for linear Manhattan plotting, 1.6× faster (and 3× faster with optional pre-filtering) for circular Manhattan, and 7.7× faster for qq rendering. Multi-track comparisons of two summary statistics are 4.5× faster (linear) and 3.5× faster (circular) than CMplot's equivalent mode. Transparent hg18/hg19 → hg38 liftover lets users mix coordinate systems within a single plot, and a lightweight bundle of Ensembl GFF3 gene information files (hg19 and hg38) enables nearest gene annotation.Availability and implementation: pycmplot is freely available under the MIT license at https://github.com/esohkevin/pycmplot; and from PyPI (pip install pycmplot). Documentation is at https://pycmplot.readthedocs.io.","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"6 1","pages":"vbag281"},"PeriodicalIF":2.6,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13641829/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

User-driven development and evaluation of an agentic framework for analysis of large pathway diagrams. 用户驱动的开发和评估用于分析大型路径图的代理框架。

IF 2.6

Bioinformatics advances Pub Date : 2026-09-21 eCollection Date: 2026-01-01 DOI: 10.1093/bioadv/vbag277

Marie Corradi, Ivo Djidrovski, Luiz Ladeira, Bernard Staumont, Anouk Verhoeven, Julen Sanz Serrano, Adrien Rougny, Ahmad Vaez, Ahmed Hemedan, Alexander Mazein, Anna Niarakis, Arthur de Carvalho E Silva, Charles Auffray, Egon Willighagen, Eliska Kuchovska, Falk Schreiber, Irina Balaur, Laurence Calzone, Lisa Matthews, Lorenzo Veschini, Marc E Gillespie, Martina Kutmon, Matthias König, Matti van Welzen, Noriko Hiroi, Oxana Lopata, Pierre Klemmer, Rupert Overall, Tim Hofer, Venkata Satagopam, Reinhard Schneider, Marc Teunis, Liesbet Geris, Marek Ostaszewski

{"title":"User-driven development and evaluation of an agentic framework for analysis of large pathway diagrams.","authors":"Marie Corradi, Ivo Djidrovski, Luiz Ladeira, Bernard Staumont, Anouk Verhoeven, Julen Sanz Serrano, Adrien Rougny, Ahmad Vaez, Ahmed Hemedan, Alexander Mazein, Anna Niarakis, Arthur de Carvalho E Silva, Charles Auffray, Egon Willighagen, Eliska Kuchovska, Falk Schreiber, Irina Balaur, Laurence Calzone, Lisa Matthews, Lorenzo Veschini, Marc E Gillespie, Martina Kutmon, Matthias König, Matti van Welzen, Noriko Hiroi, Oxana Lopata, Pierre Klemmer, Rupert Overall, Tim Hofer, Venkata Satagopam, Reinhard Schneider, Marc Teunis, Liesbet Geris, Marek Ostaszewski","doi":"10.1093/bioadv/vbag277","DOIUrl":"10.1093/bioadv/vbag277","url":null,"abstract":" As biomedical knowledge keeps growing, resources storing available information multiply and grow in size and complexity. Such resources can be in the format of molecular interaction maps, which represent cellular and molecular processes under normal or pathological conditions. However, these maps can be complex and hard to navigate, especially to novice users. Large language models (LLMs), particularly in the form of agentic frameworks, have emerged as a promising technology to support this exploration. In this article, we describe a user-driven process of prototyping, development, and user testing of Llemy, an LLM-based system for exploring these molecular interaction maps. By involving domain experts from the very first prototyping in the form of a hackathon and collecting both fine-grained and general feedback on more refined versions, we were able to evaluate the perceived utility and quality of the developed system, in particular for summarizing maps and pathways, as well as prioritize the development of future features. We recommend continued user-driven development and benchmarking to keep the community engaged. This will also facilitate the transition towards open-weight LLMs to support the needs of the open research environment in an ever-changing technology landscape.","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"6 1","pages":"vbag277"},"PeriodicalIF":2.6,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13674548/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149217369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RBApy: extending resource allocation modeling to eukaryotes in complex environments. RBApy：将资源分配模型扩展到复杂环境中的真核生物。

IF 2.6

Bioinformatics advances Pub Date : 2026-09-17 eCollection Date: 2026-01-01 DOI: 10.1093/bioadv/vbag276

Oliver Bodeit, Nadia Bessoltane, Delphine Charif, Anaghim Temtem, Olivier Inizan, Anne Goelzer

{"title":"RBApy: extending resource allocation modeling to eukaryotes in complex environments.","authors":"Oliver Bodeit, Nadia Bessoltane, Delphine Charif, Anaghim Temtem, Olivier Inizan, Anne Goelzer","doi":"10.1093/bioadv/vbag276","DOIUrl":"https://doi.org/10.1093/bioadv/vbag276","url":null,"abstract":"Motivation: Resource allocation modeling-as the Resource Balance Analysis (RBA) framework-provides a way to understand and predict how limited cellular resources (e.g. energy, proteins, etc.) in cells are distributed among competing cell processes within a limited cellular space. Currently, resource allocation modeling for eukaryotes remains limited due to the lack of software capable of generating calibrated RBA models for these types of cells, unlike prokaryotes, which benefit from the software tools such as RBApy, RBAtools, and the RBAml format for model encoding.Results: Here, we extended the RBA toolkit (RBApy, RBAtools, and RBAml) to account for specific aspects of eukaryotic cells growing in complex environments such as varying temperature, light, or nutritional conditions. We used them to generate and simulate RBA models of both prokaryotic (Escherichia coli) and eukaryotic (Arabidopsis thaliana) cells for varying temperatures. The resulting models show excellent prediction capabilities when benchmarked against published experimental datasets. The upgraded RBA toolkit will pave the way to creating, calibrating, and running resource allocation models for crops, livestock, or humans for a wide range of medical, biotechnological, or agricultural applications in the future.Availability and implementation: RBApy and RBAtools are available via PyPI and at https://github.com/RBAgroup.","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"6 1","pages":"vbag276"},"PeriodicalIF":2.6,"publicationDate":"2026-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13626133/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

pykarambola: Minkowski tensor morphometry of 3D structures. pykarambola：三维结构的闵可夫斯基张量形态计量学。

IF 2.6

Bioinformatics advances Pub Date : 2026-09-17 eCollection Date: 2026-01-01 DOI: 10.1093/bioadv/vbag273

Yajushi Khurana, Keisuke Ishihara

{"title":"pykarambola: Minkowski tensor morphometry of 3D structures.","authors":"Yajushi Khurana, Keisuke Ishihara","doi":"10.1093/bioadv/vbag273","DOIUrl":"10.1093/bioadv/vbag273","url":null,"abstract":"Motivation: Three-dimensional biological morphologies encode functional and physiological state, yet their directional, orientational, and topological properties are rarely captured by morphometric tools in bioimage analysis. Minkowski tensors encode surface curvature and directionality for arbitrary topologies; their eigensystems directly quantify elongation axes and anisotropy. A C++ implementation, karambola, computes Minkowski tensors for triangulated surfaces but is inaccessible within Python-based bioimage workflows.Results: We present pykarambola, a Python package that accepts NumPy arrays and standard mesh formats and returns Minkowski tensors, including derived anisotropy and orientation quantities. A high-level label-image interface converts 3D integer arrays into per-object Minkowski tensors in a single call, making pykarambola directly compatible with the output of segmentation tools. An optional Cython extension accelerates graph-traversal steps of mesh initialization for large-scale analyses. Validated on synthetic meshes spanning three topologies and benchmarked on 1584 adrenal gland meshes, pykarambola reproduces all 121 karambola features to near-floating-point agreement and is 2.8-fold faster, with speedups primarily attributable to per-object file input/output.Availability and implementation: pykarambola is distributed under the BSD 3-Clause License and is available on GitHub at https://github.com/Ishihara-SynthMorph/pykarambola. It can be installed via pip.","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"6 1","pages":"vbag273"},"PeriodicalIF":2.6,"publicationDate":"2026-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13668341/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149198200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0