Frontiers in bioinformatics最新文献

{"title":"Editorial: Integrative single-cell and spatial multiomics: charting cellular architecture and disease microenvironments.","authors":"Wenchong Chen, Jingjing Lu, Wancheng Guo, Boyu Li, Hang Zhang, Yilin Wang, Zhaokai Zhou, Ran Xu","doi":"10.3389/fbinf.2026.1983096","DOIUrl":"10.3389/fbinf.2026.1983096","url":null,"abstract":"","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"6 ","pages":"1983096"},"PeriodicalIF":3.6,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13593905/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149026767","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}

{"title":"Architectural good practices for reproducible benchmarking in protein machine learning.","authors":"Julián García-Vinuesa, Diego Fernández-Villegas, Michelle Soto-García, Xavier Cadet, Mehdi D Davari, Frederic Cadet, Juan A Asenjo, Roberto Uribe-Paredes, David Medina-Ortiz","doi":"10.3389/fbinf.2026.1925740","DOIUrl":"10.3389/fbinf.2026.1925740","url":null,"abstract":"<p><p>Reliable benchmarking in protein machine learning requires biological tasks, datasets, representations, execution conditions, and evaluation regimes to be explicitly defined and traceable. Protein-specific dependencies, including label semantics, negative-class construction, evolutionary relationships, similarity control, inferred structures, protein language model configurations, and potential pretraining contamination, can alter benchmark interpretation. This Perspective provides an operational, protein-specific synthesis of established reproducibility practices through an artefact-linked architecture. We define five core requirements for verifiable benchmarking, including deterministic curation, persistent and versioned artefacts, explicit interface contracts, reproducible execution, and transparent evaluation. Prediction provenance, uncertainty, calibration, and explainability are treated as an additional decision-readiness layer. These requirements are translated into minimum records, provenance links, and verification checks. An antimicrobial peptide classification case study demonstrates their application to alternative task formulations, negative-class definitions, dataset compositions, and partitioning strategies within a controlled workflow.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"6 ","pages":"1925740"},"PeriodicalIF":3.6,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13593872/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149027243","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}

{"title":"In silico transcriptomic analysis nominates TSPAN32 as a central node of SCFA-driven immunometabolic reprogramming in intestinal epithelial cells.","authors":"Zahra Masood, Iqra Sarwar, Ayesha Sanam, Amber Zaidi, Muhammad Zulfiqah Sadikan","doi":"10.3389/fbinf.2026.1847552","DOIUrl":"10.3389/fbinf.2026.1847552","url":null,"abstract":"<p><strong>Introduction: </strong>Microbial short-chain fatty acids (SCFAs) regulate intestinal epithelial homeostasis and immune tolerance. Yet, the specific host effector genes that mediate these responses remain poorly defined, limiting the identification of biomarkers and therapeutic targets.</p><p><strong>Methods: </strong>A multi-layered <i>in silico</i> analysis was performed on publicly available transcriptomic data (GEO: GSE200309) derived from human intestinal epithelial cells exposed to a physiologic acetate-propionate-butyrate mixture (n = 6 treated; n = 6 controls). Differential expression was assessed using a two-sample Student's t-test with Benjamini-Hochberg FDR correction. A dual-threshold strategy distinguished statistically robust genes (FDR <0.05) from exploratory, hypothesis-generating candidates (nominal p < 0.05). Functional enrichment (Enrichr; GO-BP, KEGG, Reactome), transcription-factor inference (ChEA3/TRRUST), PPI network analysis (STRING v12/Cytoscape), gene-disease mapping (DisGeNET/Open Targets), and in-sample ROC modeling were subsequently applied.</p><p><strong>Results: </strong>Under FDR correction, TSPAN32 emerged as the sole transcriptome-wide significant gene following SCFA exposure (log₂FC = +1.03; FDR = 0.043; Cohen's d ≈ 4.4), corresponding to an approximately 2.04-fold increase in expression. At the exploratory threshold, 69 additional DEGs were identified (31 upregulated, 38 downregulated; nominal p < 0.05), implicating histone acetylation, chromatin remodeling, microRNA biogenesis, and suppression of pro-inflammatory and apoptotic signaling. Network analysis positioned TSPAN32 as the highest-ranked hub within an immunometabolic subnetwork connecting metabolic regulators (PPARG, PPARGC1A, PLIN2), inflammatory mediators (NFKB1, RELB, IL6ST, IL10RA), epigenetic regulators (SIRT1, HDAC9), and redox-response genes (HMOX1, TXNIP). In-sample ROC analysis showed strong discrimination between SCFA-treated and control samples (AUC = 0.91; 95% CI: 0.85-0.98; sensitivity = 0.92; specificity = 0.88; accuracy = 0.90). To extend mechanistic inference, computational TSPAN32 knockdown was simulated by removing TSPAN32 from the STRING-derived network. This perturbation reduced network edges by 45.5%, average degree by 41.8%, largest connected component size by 56.3%, and global efficiency by 66.6%, while increasing the number of disconnected components from 1 to 5. These findings support TSPAN32 as a predicted network-stabilizing node rather than merely a differentially expressed transcript.</p><p><strong>Conclusion: </strong>These hypothesis-generating findings nominate TSPAN32 as the primary SCFA-responsive effector gene in intestinal epithelial cells, coordinating epigenetic remodeling and immunometabolic reprogramming. Causal validation through functional perturbation and independent cohort replication is required before clinical translation.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"6 ","pages":"1847552"},"PeriodicalIF":3.6,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13593874/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149026772","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}

{"title":"Revealing RELL1 signaling relying on the phosphoregulatory network analysis.","authors":"Pathiyil Sajini Sekhar, Diya Sanjeev, Amal Fahma, Suhail Subair, Athira Perunally Gopalakrishnan, Prathik Basthikoppa Shivamurthy, Rajesh Raju, Sowmya Soman","doi":"10.3389/fbinf.2026.1939325","DOIUrl":"10.3389/fbinf.2026.1939325","url":null,"abstract":"<p><strong>Introduction: </strong>RELL1 (Receptor Expressed in Lymphoid Tissues-Like 1) is a member of the TNF receptor superfamily. Although the physiological ligands and mechanistic insights into cell signaling still remain to be elucidated, its over-expression is associated with poor prognosis and enhanced immune cell infiltration in cancers, marking it a potential oncogenic driver and immunotherapeutic target. Despite extensive phosphoproteomic evidence indicating that RELL1 undergoes phosphorylation, the functional significance of its phosphosites has not been systematically investigated.</p><p><strong>Methods: </strong>Global human phosphoproteomic datasets were systematically analyzed to identify predominant RELL1 phosphosites. The two most frequently detected phosphosites were selected as predominant sites for phosphosite-centric analysis. To explore their functional significance, their highly co-phosphoregulated sites in other proteins across diverse conditions were examined. A stringent criteria was applied to determine protein phosphosites that showed either positive or negative co-regulation with predominant sites. These co-regulated sites were further analyzed within known interacting proteins, and predicted the upstream regulators of RELL1, followed by enrichment analysis.</p><p><strong>Results: </strong>Exemplified by the detection of its phosphorylated forms in 474 qualitative and 150 quantitative phosphoproteomic datasets across multiple experimental conditions, we propose phosphorylation as a potential regulatory mechanism associated with RELL1 function. However, the functional role of any of the phosphosites in RELL1 phosphosites remains unknown. Among the detected phosphosites, S244 and S161 were the most frequently observed sites perturbed across datasets, and hence, considerably the predominant sites. Co-phosphoregulation analysis revealed plausible regulatory networks comprising interacting proteins and predicted upstream kinases. Bioinformatics analyses revealed strong associations between these phosphosites and biological processes such as nuclear transport and cell cycle regulation.</p><p><strong>Conclusion: </strong>This systems-level phosphoproteomic investigation provides the potential phosphoregulatory map for RELL1 phosphosites, which could lay a foundation for further experimental investigations as well as in establishing its functional roles contributing to advancements in RELL1 signaling events relevant to immuno-oncotherapy.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"6 ","pages":"1939325"},"PeriodicalIF":3.6,"publicationDate":"2026-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13590554/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149018742","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}

{"title":"Alternative splicing remodeling and splicing factor regulatory networks define immune-associated molecular heterogeneity in dilated cardiomyopathy.","authors":"Jia Li, Yiyu He, Xianxian Zhao, Zhifu Guo, Jinchao Song, Xiaowei Song","doi":"10.3389/fbinf.2026.1934275","DOIUrl":"10.3389/fbinf.2026.1934275","url":null,"abstract":"<p><p>Dilated cardiomyopathy (DCM), a progressive cardiac disorder marked by ventricular dilatation and systolic dysfunction, involves a complex interplay between genetic and immune dysregulation. However, how alternative splicing remodeling contributes to its molecular heterogeneity remains poorly understood. Here, we performed an integrated transcriptomic analysis to characterize DCM-associated alternative splicing landscapes and their regulation by splicing factor networks. We identified widespread differential alternative splicing (DAS) events in DCM, with affected genes significantly enriched in cardiac contraction, sarcomere organization, calcium handling, extracellular matrix remodeling, and protein metabolism. Representative splicing events in key cardiac genes, including <i>TTN</i>, <i>RYR2</i>, <i>LDB3</i>, and <i>FLNA</i>, exhibited distinct junction usage and percent spliced in (PSI) alterations between DCM and control samples, suggesting functionally relevant transcript isoform remodeling. By integrating splicing factor expression profiles with DAS event PSI values, we constructed a characteristic SF-AS regulatory network and identified five key splicing factors-<i>MBNL1</i>, <i>NOVA1</i>, <i>RBM25</i>, <i>RBM5</i>, and <i>SF1</i>-as candidate tissue-level biomarkers of DCM-associated splicing remodeling. Molecular subtype analysis further revealed distinct DCM subgroups characterized by divergent immune infiltration patterns, pathway activities, and hub gene signatures. Machine learning-based identification and external validation supported the diagnostic potential of this five-splicing-factor signature. Collectively, this study deciphers coordinated splicing factor-associated alternative splicing remodeling in DCM, providing deeper insights into the immune-associated molecular heterogeneity and potential regulatory mechanisms underlying disease progression.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"6 ","pages":"1934275"},"PeriodicalIF":3.6,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13585734/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149009036","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}

{"title":"Computational insights into synergistic mechanisms of PD-901 and 5-azacitidine targeting PTPN11 (SHP2) E76K mutation in juvenile myelomonocytic leukemia.","authors":"Abeer M Al-Subaie, Balu Kamaraj","doi":"10.3389/fbinf.2026.1887328","DOIUrl":"10.3389/fbinf.2026.1887328","url":null,"abstract":"<p><strong>Introduction: </strong>Juvenile Myelomonocytic Leukemia (JMML) is an aggressive pediatric hematological cancer categorized by aberrant activation of the RAS/MAPK pathway. It is commonly caused by gain-of-function mutations, such as E76K in the PTPN11 protein. While 5-azacitidine (5-Aza) and the MEK inhibitor PD0325901 (PD-901) are not known direct inhibitors of SHP2/PTPN11, the reported activity of 5-Aza combined with MEK inhibition in PTPN11-mutated JMML offered a biological rationale for examining their potential structural interactions with SHP2.</p><p><strong>Methods: </strong>This study used a computational approach that included molecular docking, molecular dynamics (MD) simulations, and binding free-energy calculations using the MM-PBSA method to exploratively investigate interactions between 5-azacitidine (5-Aza) and the MEK inhibitor PD0325901 (PD-901) with wild-type and E76K-mutant PTPN11 proteins.</p><p><strong>Results: </strong>In the molecular docking study, 5-Aza was observed to bind within the active site, whereas PD-901 bound preferentially to the allosteric site. The dual-ligand simulations were used to investigate whether occupancy of these distant regions was associated with changes in PTPN11's structural and dynamic characteristics. MD simulations showed that the structures of all complexes remained stable throughout, and that the combined structure exhibited lower deviations, less residue flexibility, compactness, and more intermolecular hydrogen-bond interactions. Principal component analysis also revealed differences in the dominant conformational motions of the ligand-bound systems. MM-PBSA calculations provided comparative estimates of binding energetics and revealed promising interaction energies for all complexes, particularly in the E76K mutant system.</p><p><strong>Discussion: </strong>Overall, these computational findings suggest that the association of 5-Aza and PD-901 with distinct regions of PTPN11 may influence its structural and dynamic properties. These findings should therefore be considered exploratory and do not establish direct SHP2 binding or inhibition by either compound. Further biochemical, biophysical, and cellular studies are needed to validate these predicted interactions and determine their potential biological or therapeutic relevance in JMML.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"6 ","pages":"1887328"},"PeriodicalIF":3.6,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13586710/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149009041","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}

{"title":"Identifying mounting behaviour in boars using deep learning-based instance segmentation and binary classification - a pilot study.","authors":"Harry Aricibasi, Jessica Bode, Renée Bergeron, Dan Tulpan","doi":"10.3389/fbinf.2026.1869902","DOIUrl":"10.3389/fbinf.2026.1869902","url":null,"abstract":"<p><strong>Introduction: </strong>Mounting behaviour in group-housed pigs poses significant welfare and productivity challenges, often resulting in injuries and stress. To address this issue, we developed a novel computer vision-based approach for the automatic detection of mounting behaviour in pigs.</p><p><strong>Methods: </strong>The pilot study was conducted on eight boars, aged 4-5 months and weighing between 60 and 90 kg, housed in two groups of four. Continuous video footage was collected over a 1-week period using an overhead camera, resulting in 766 2-s video clips. The proposed hybrid approach integrates Mask Region-based Convolutional Neural Network (Mask R-CNN) instance segmentation with a binary classifier. To evaluate the model's performance under varying data conditions, the dataset was divided into training, validation, and testing sets using three data grouping scenarios: by frame, by clip, and by day.</p><p><strong>Results: </strong>Among the five evaluated binary classification algorithms, Support Vector Machine (SVM) was selected based on its superior performance. The hybrid system achieved a balanced accuracy and F1-score of 95% with the clip-based split, rising to 99% with the frame-based split and falling to 74% with the day-based split.</p><p><strong>Discussion: </strong>Under pilot conditions, the system offers a feasible proof-of-concept for continuous monitoring of mounting behaviour in group-housed pigs, operating at a processing rate of five frames per second. This capability offers strong potential for supporting early intervention and proactive welfare management, subject to future multi-site validation. Moving forward, future research will focus on integrating individual animal tracking and conducting larger-scale studies to further explore the system's scalability and enhance its performance.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"6 ","pages":"1869902"},"PeriodicalIF":3.6,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13587698/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149009076","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}

{"title":"Conformational dynamics of fuzzy interfaces in disordered protein complexes: mapping key residues and binding modes beyond NMR models.","authors":"María Laura Fernández, María Clara Bastien, Franco G Tavolaro, Cristina Marino-Buslje","doi":"10.3389/fbinf.2026.1907936","DOIUrl":"10.3389/fbinf.2026.1907936","url":null,"abstract":"<p><p>Understanding the dynamic behavior of fuzzy complexes formed by intrinsically disordered proteins (IDPs) is challenging due to their conformational flexibility. Nuclear Magnetic Resonance (NMR) structural bundles satisfy experimental constraints and inherently provide an overview of alternative conformations in solution. However, they assign equal weight to every sampled model, obscuring the temporal prevalence and dynamics of inter-residue contacts. In this study, we performed dual 1-microsecond (µs) Molecular Dynamics (MD) simulations for eight biologically relevant fuzzy complexes, utilizing the most distant conformers from deposited NMR models, as starting configurations. Through structural clustering and contact-persistence analysis, we classified the complexes into two distinct dynamic categories. The first group comprises complexes whose trajectories remain consistent with experimental data. Notably, large-scale motions such as relative chain rotations observed during simulations are already reflected as distinct orientations within the starting NMR conformers. Conversely, the second group comprises complexes that exhibit interaction modes absent in the structural NMR ensembles. These include alternative stable interfaces arising from chain reorientation, as well as highly dynamic interfaces characterized by rapidly exchanging contacts lacking any persistent stabilizing core. Furthermore, the microsecond trajectories captured intermittent dissociation and re-association events where the proteins sampled transient contacts through alternative regions. Overall, leveraging NMR models as a baseline for MD clustering and contact weighting, provides a systematic bioinformatics analysis to solve the atomistic details of flexible interfaces. Beyond categorizing diverse binding behaviors, this approach systematically refines the interaction surfaces across all studied cases, uncovers dynamic features that escape detection in ensemble-averaged NMR structures. Furthermore, it maps key residues to guide further experimental approaches, such as mutational studies or therapeutic targeting, among other applications.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"6 ","pages":"1907936"},"PeriodicalIF":3.6,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13582614/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148992900","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}

{"title":"All-atoms MD simulations study of newly designed ciprofloxacin derivatives as potential bacterial DHPS and DNA gyrase inhibitors.","authors":"Chita Ranjan Sahoo, Madhusmita Rout, Sudhir Kumar Paidesetty, Budheswar Dehury, Debdutta Bhattacharya, Sanghamitra Pati","doi":"10.3389/fbinf.2026.1876643","DOIUrl":"10.3389/fbinf.2026.1876643","url":null,"abstract":"<p><p>The widespread use of antibiotics, particularly ciprofloxacin, has accelerated the emergence of antibiotic-resistant bacteria, posing a major public health challenge. Limited investment and declining pharmaceutical interest have slowed the discovery of new antibiotics, contributing to the increasing prevalence of multidrug-resistant (MDR) infections, especially those caused by ESKAPE pathogens. Uropathogenic <i>Escherichia coli</i> (UPEC), a leading cause of urinary tract infections (UTIs), develops multidrug resistance through mechanisms including drug target modification and reduced antibiotic susceptibility. In the present study, a series of ciprofloxacin-sulfonamide hybrid molecules (CIS1-CIS15) was designed, in which each pharmacophore retains its established mechanism of action. Ciprofloxacin inhibits DNA gyrase and topoisomerase IV, whereas sulfonamides inhibit dihydropteroate synthase (DHPS) by competing with para-aminobenzoic acid (PABA) in the bacterial folate biosynthetic pathway. Accordingly, the designed hybrids were computationally evaluated against both enzymatic targets to investigate their potential dual-target antibacterial activity. Molecular docking and molecular dynamics (MD) simulations were performed to assess the binding affinity and stability of the ciprofloxacin-bearing sulfonamide derivatives (CIS1-CIS15) against DNA gyrase and <i>Staphylococcus aureus</i> DHPS. Principal component analysis (PCA) and free-energy landscape (FEL) analysis were used to characterize the conformational flexibility and low-energy states of the protein-ligand complexes, while MD simulations validated the stability of the highest-scoring docked complexes. Among the designed derivatives, CIS4 (ciprofloxacin-sulfamethoxazole), CIS5 (ciprofloxacin-sulfaguanidine), and CIS12 (ciprofloxacin-sulfamerazine) exhibited the strongest binding affinity toward both targets while maintaining conformational stability throughout the simulations. Structural analysis of the pre- and post-MD trajectories identified Arg52, Lys39, Arg88, Lys94, Lys120, Glu201, and Lys203 as key residues involved in ligand recognition. Overall, CIS4, CIS5, and CIS12 emerged as the most promising dual-target inhibitor of bacterial DHPS and DNA gyrase. These findings provide valuable structural insights for the rational design of novel fluoroquinolone-based antibacterial agents and demonstrate the utility of computational approaches in identifying potential therapeutics against drug-resistant bacterial pathogens.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"6 ","pages":"1876643"},"PeriodicalIF":3.6,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13582570/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148992935","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}

{"title":"Software engineering for reproducible pipeline development in bioinformatics.","authors":"Daniel Pérez-Rodríguez, Alba Nogueira-Rodríguez, Jorge Vieira, Cristina P Vieira, Daniel Glez-Peña, Hugo López-Fernández","doi":"10.3389/fbinf.2026.1824590","DOIUrl":"10.3389/fbinf.2026.1824590","url":null,"abstract":"<p><p>Reproducibility in bioinformatics remains challenging despite the availability of workflow management systems and mature computational infrastructures. This work presents a software-engineering perspective for developing reproducible bioinformatics pipelines, with emphasis on pipeline-specific code. We reinterpret the SOLID principles in this context at two levels: workflow management systems (e.g., Nextflow, Snakemake, and Compi) and pipeline implementation. Our approach promotes pipeline designs based on well-defined task interfaces, explicit input/output specifications, and a clear separation between compute tasks and glue/adaptation tasks, in order to improve flexibility, reuse, and maintainability. The paper provides practical guidance for robust and reproducible pipeline development, including systematic validation checks (environment, inputs, and runtime), standardized project organization, and comprehensive testing strategies using both real and synthetic data within continuous integration workflows. It also discusses how modular ecosystems (such as nf-core modules and Snakemake wrappers) support these principles in community-driven environments. Finally, we relate these recommendations to FAIR-oriented research software guidelines (FAIR4RS and FAIRsoft), showing how core engineering practices strengthen robustness, portability, and long-term sustainability, thereby supporting reproducibility in bioinformatics pipelines.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"6 ","pages":"1824590"},"PeriodicalIF":3.6,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13582464/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148992941","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}