Computational and structural biotechnology journal最新文献

{"title":"Beyond sequence: A physics-informed machine learning framework for predicting DNA mutations.","authors":"M Suárez-Villagrán, N Mitsakos, J H Miller","doi":"10.1016/j.csbj.2025.08.033","DOIUrl":"10.1016/j.csbj.2025.08.033","url":null,"abstract":"<p><p>This paper investigates how incorporating information from a quantum tight-binding model can enhance the predictive capability of machine learning models for identifying mutation-prone sites in mitochondrial DNA (mtDNA). We employ quantum Hamiltonian techniques and machine learning to explore mutations in mitochondrial DNA's hypervariable segment 1 (HVR1). This region is recognized for its high variability and is frequently used in genealogical DNA testing and research. Our approach considers the local energy associated with each base pair, as well as the interactions among electrons within the DNA chain. For this study, we analyze data from the Mitomap database. Our findings suggest that both the local ionization energies and the context-dependent nature of the base pairs significantly influence the locations of mutations within DNA. Specifically, our machine learning model can extract valuable insights when examining homopolymeric runs-regions where a single base pair repeats multiple times within a sequence.</p>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"3985-3992"},"PeriodicalIF":4.1,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12465030/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145184743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of shared and unique mechanisms of atopic dermatitis and ulcerative colitis by construction and computational analysis of disease maps.","authors":"Oxana Lopata, Marcio Luis Acencio, Xinhui Wang, Ahmed Abdelmonem Hemedan, Michael J Chao, Scott A Jelinsky, Florian Tran, Philip Rosenstiel, Andrew Y F Li Yim, Reinhard Schneider, Venkata Satagopam, Marek Ostaszewski","doi":"10.1016/j.csbj.2025.09.008","DOIUrl":"10.1016/j.csbj.2025.09.008","url":null,"abstract":"<p><p>Atopic dermatitis (AD) and ulcerative colitis (UC) are immune-mediated inflammatory diseases (IMIDs) with high prevalence and treatment costs. AD mainly affects the skin, while UC targets the colon and rectum, but both are characterised by immune dysregulation driven by aberrant T helper cell activation, persistent barrier dysfunction, genetic predisposition, and environmental triggers. This overlap may explain the link between the two diseases and the increased risk of UC in patients with AD. Both diseases are chronic, progressive, and limited in treatment options, and there is a need for a better understanding of their mechanisms and biomarkers. To address this, we developed disease maps for UC and AD, covering their molecular mechanisms. Here, we present the development and contents of the maps, as well as demonstrate their application in data visualisation and analysis. Our systematic, interactive comparison reveals both common and disease-specific signatures, as well as common pathological pathways. These findings highlight shared biomarkers for predicting progression and therapy outcomes, and opportunities for drug repurposing. The UC and AD disease maps provide a valuable resource for representing and exploring common and distinct mechanisms, helping to advance IMID management from organ-based symptom relief towards mechanism-based treatments.</p>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"4007-4018"},"PeriodicalIF":4.1,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12465054/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145184789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"OncoProExp: An interactive shiny web application for comprehensive cancer proteomics and phosphoproteomics analysis.","authors":"Edris Sharif Rahmani, Prakash Lingasamy, Soheila Khojand, Ankita Lawarde, Sergio Vela Moreno, Andres Salumets, Vijayachitra Modhukur","doi":"10.1016/j.csbj.2025.08.038","DOIUrl":"10.1016/j.csbj.2025.08.038","url":null,"abstract":"<p><p>Cancer research has been revolutionized by mass spectrometry (MS)-based proteomics, enabling large-scale profiling of proteins and post-translational modifications (PTMs) to identify critical alterations in cancer signaling pathways. However, the lack of comprehensive, user-friendly platforms for integrative analysis limits efficient data exploration, biomarker discovery, and translational insights. To address this, we developed OncoProExp, a Shiny-based interactive web application for in-depth cancer proteomic and phosphoproteomic analyses. OncoProExp offers robust workflows for data preprocessing, interactive visualizations (PCA, hierarchical clustering, heatmaps, gene set enrichment analysis (GSEA)), and functional annotation of gene expression data. Differential expression analysis facilitates biomarker and therapeutic target discovery, while survival analysis identifies proteins whose expression stratifies overall survival, and pan-cancer exploration integrates clinical proteomic and phosphoproteomic datasets. OncoProExp also incorporates state-of-the-art predictive modeling, including Support Vector Machines (SVMs), Random Forests, and Artificial Neural Networks (ANNs) to classify cancer types from proteomic and phosphoproteomic profiles. These models were enhanced by SHapley Additive exPlanations (SHAP) for interpretability. To enhance its translational utility, OncoProExp supports user-uploaded data, protein-protein interactions, pathway enrichment, drug relevance evaluation, and clinical annotation analysis. OncoProExp is deployable via Docker containers, ensuring flexible and scalable integration into individual servers. Its utility has been demonstrated using Clinical Proteomic Tumor Analysis Consortium (CPTAC) datasets. OncoProExp is freely accessible at https://oncopro.cs.ut.ee/ without login requirements, offering a comprehensive resource for translational cancer research.</p>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"3993-4006"},"PeriodicalIF":4.1,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12465049/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145184784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to \"Maternal <i>Clostridium butyricum</i> supplementation during late gestation and lactation enhances gut bacterial communities, milk quality, and reduces piglet diarrhea\" [Comput Struct Biotechnol J 27 (2025) 2933-2945].","authors":"Morakot Nuntapaitoon, Piraya Chatthanathon, Matanee Palasuk, Alisa Wilantho, Jakavat Ruampatana, Sissades Tongsima, Sarn Settachaimongkon, Naraporn Somboonna","doi":"10.1016/j.csbj.2025.09.005","DOIUrl":"https://doi.org/10.1016/j.csbj.2025.09.005","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.1016/j.csbj.2025.06.040.].</p>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"3803"},"PeriodicalIF":4.1,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12451280/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145130382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Embedding a feruloyl esterase active site into a thermophilic endoxylanase scaffold for the degradation of feruloylated xylans.","authors":"Rubén Muñoz-Tafalla, Isabel Cea-Rama, Fadia V Cervantes, Jose L Gonzalez-Alfonso, Francisco J Plou, Julio Polaina, Julia Sanz-Aparicio, Manuel Ferrer, Víctor Guallar, David Talens-Perales","doi":"10.1016/j.csbj.2025.09.003","DOIUrl":"10.1016/j.csbj.2025.09.003","url":null,"abstract":"<p><p>The structural complexity of xylan makes its complete degradation challenging. Strategies to improve its hydrolysis often requires enzyme cocktails with multiple specific activities or proteins harboring multiple catalytic domains. Here, we introduce a novel approach through the design of Xyn11_m1, a multifunctional enzyme that combines endoxylanase and feruloyl esterase activities, two catalytic functions involved in the hydrolysis of feruloylated xylans. Using the PluriZyme concept, an artificial feruloyl esterase active site was engineered into the scaffold of a thermophilic glycoside hydrolase family 10 xylanase, Xyn11, from <i>Pseudothermotoga thermarum</i>. Computational design, guided by protein energy landscape exploration simulations, revealed a surface cavity that could accommodate feruloyl-L-arabinose and a xylopentaose (a 5-xylose xylan polymer) bearing a single feruloyl-L-arabinose substitution on the central xylose unit. This cavity was subsequently remodeled into a serine-histidine-aspartic/glutamic acid catalytic triad with feruloyl esterase activity. Molecular dynamics simulations confirmed the stability of the engineered active site. Xyn11_m1 was successfully produced, crystallized, and characterized, and its xylanase activity at 90 °C against oat spelt xylan was comparable to that of the wild-type enzyme (713 ± 4 vs. 600 ± 8 units/mg), and it also displayed feruloyl esterase activity against methyl ferulate (140 ± 5 units/mg), a capability lacking in Xyn11. Notably, Xyn11_m1 exhibited approximately 2.5-fold greater activity compared with Xyn11 (513 ± 27 vs. 222 ± 9 units/mg) against wheat bran xylan containing ferulic acid ester linked to arabinofuranosyl residues. This dual functionality enables efficient degradation of feruloylated xylans, highlighting the potential of PluriZymes to advance biomass deconstruction technologies.</p>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"3814-3823"},"PeriodicalIF":4.1,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12454871/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145136691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Internal validation strategy for high dimensional prognosis model: A simulation study and application to transcriptomic in head and neck tumors.","authors":"Antoine Dubray-Vautrin, Victor Gravrand, Grégoire Marret, Constance Lamy, Jerzy Klijanienko, Sophie Vacher, Ladidi Ahmanache, Maud Kamal, Olivier Choussy, Nicolas Servant, Célia Dupain, Christophe Le Tourneau, Jimmy Mullaert","doi":"10.1016/j.csbj.2025.08.035","DOIUrl":"10.1016/j.csbj.2025.08.035","url":null,"abstract":"<p><strong>Background: </strong>Predictive models using high-dimensional data, such as genomics and transcriptomics, are increasingly used in oncology for time-to-event endpoints. Internal validation of these models is crucial to mitigate optimism bias prior to external validation. Common strategies include train-test, bootstrap, and (nested) cross-validation. However, no benchmark exists for these methods in high-dimensional settings. We aimed to compare these strategies and provide recommendations in the field of transcriptomic analysis.</p><p><strong>Method: </strong>A simulation study was conducted using data from the SCANDARE head and neck cohort (NCT03017573) including n = 76 patients. Simulated datasets included clinical variables (age, sex, HPV status, TNM staging), transcriptomic data (15,000 transcripts), and disease-free survival, with a realistic cumulative baseline hazard. Sample sizes of 50, 75, 100, 500, and 1000 were simulated, with 100 replicates each. Cox penalized regression was performed for model selection, followed by train-test 70 % training), bootstrap (100 iterations), 5-fold cross-validation, and nested cross-validation (5 ×5) to assess discriminative (time-dependent AUC and C-Index) and calibration (3-year integrated Brier Score) performance.</p><p><strong>Results: </strong>Train-test validation showed unstable performance. Conventional bootstrap was over-optimistic, while the 0.632 + bootstrap was overly pessimistic, particularly with small samples (n = 50 to n = 100). The k-fold cross-validation and nested cross-validation improved performance with larger sample sizes, with k-fold cross-validation demonstrating greater stability. Nested cross-validation showed performance fluctuations depending on the regularization method for model development.</p><p><strong>Conclusion: </strong>The K-fold cross-validation and nested cross-validation are recommended for internal validation of Cox penalized models in high-dimensional time-to-event settings. These methods offer greater stability and reliability compared to train-test or bootstrap approaches, particularly when sample sizes are sufficient.</p>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"3792-3802"},"PeriodicalIF":4.1,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12451366/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145130408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Smmit: A pipeline for integrating multiple single-cell multi-omics samples.","authors":"Changxin Wan, Zhicheng Ji","doi":"10.1016/j.csbj.2025.08.020","DOIUrl":"10.1016/j.csbj.2025.08.020","url":null,"abstract":"<p><p>Multi-sample single-cell multi-omics datasets, which simultaneously measure multiple data modalities in the same cells across multiple samples, facilitate the study of gene expression, gene regulatory activities, and protein abundances on a population scale. We developed Smmit, a computational pipeline for integrating data both across samples and modalities. Compared to existing methods, Smmit more effectively removes batch effects while preserving relevant biological information, resulting in superior integration outcomes. Additionally, Smmit is more computationally efficient and builds upon existing computational methods, requiring minimal effort for implementation. While the focus of Smmit is not algorithmic innovation, it provides an empirically useful solution for analyzing multi-sample single-cell multi-omics data. Smmit is an R software package that is freely available on GitHub: https://github.com/zji90/Smmit.</p>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"3785-3791"},"PeriodicalIF":4.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12451375/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145130449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genomic, structural, and molecular analysis of calmodulin-binding transcriptional activators (CAMTAs) suggests their role in plant development and abiotic stress tolerance in chickpea.","authors":"Kamankshi Sonkar, Saravanappriyan Kamali, Atul Kumar, Deepika Deepika, Ankit Ankit, Amarjeet Singh","doi":"10.1016/j.csbj.2025.08.032","DOIUrl":"10.1016/j.csbj.2025.08.032","url":null,"abstract":"<p><p>The calmodulin-binding transcriptional activator (CAMTA) transcription factors regulate the expression of target genes in Ca^2 + dependent cellular functions. CAMTAs are known to regulate biotic and abiotic stress tolerance, and development in plants. CAMTA family has been characterized in Arabidopsis, it is yet to be explored in the legume plant chickpea. Here, we have identified and characterized the chickpea CAMTA family. Total seven <i>CAMTA</i> genes (<i>CaCAMTA1-7</i>) were identified in chickpea. Gene and domain structure analyses suggested that CAMTAs are structurally conserved. The phylogenetic analysis demarcated CaCAMTAs into three groups namely; group I, II and III, and indicated that CaCAMTAs have co-evolved in dicot leguminous plants whereas, they have divergent evolution in monocots. Protein homology modeling revealed their three-dimensional structure, and composition & conformations of α-helix, β-sheets and p-loops. Subcellular localization showed that CaCAMTA4 was localized both, in the nucleus and the cytosol whereas, CaCAMTA5 was localized in the nucleus. CaCAMTA promoters contain various <i>cis</i>-regulatory elements related to abiotic stresses and plant development. Expression profiling using RNA-seq data revealed differential expression of CaCAMTAs during various stages of plant development. RT-qPCR expression analysis showed that most <i>CaCAMTA</i> genes are drought, salt, and ABA responsive, suggesting their role in abiotic stress tolerance in chickpea. Moreover, CaCAMTA regulon was identified based on the presence of CAMTA binding motif (CGCG box) in the promoters of target genes, and <i>in-silico</i> interaction analysis of TF and putative targets. Overall, CaCAMTAs are crucial for abiotic stress tolerance and plant development in chickpea. Key <i>CaCAMTA</i> genes will be functionally characterized, and will be exploited for developing stress tolerant chickpea varieties.</p>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"3824-3836"},"PeriodicalIF":4.1,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12455000/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145136666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical modeling of immunoprecipitation efficiency of MeRIP-seq data enabled accurate detection and quantification of epitranscriptome.","authors":"Haozhe Wang, Kunqi Chen, Zhen Wei, Bowen Song, Manli Zhu, Jionglong Su, Anh Nguyen, Jia Meng, Yue Wang","doi":"10.1016/j.csbj.2025.08.030","DOIUrl":"10.1016/j.csbj.2025.08.030","url":null,"abstract":"<p><strong>Background: </strong>Recent advancements in epitranscriptomics highlight reversible RNA modifications as crucial regulators, with N6-methyladenosine (m⁶A) being abundant in eukaryotic mRNAs. Immunoprecipitation (IP) with specific antibodies is one of the most prevalent methods for m⁶A profiling, enabling the isolation of modified RNA for downstream analysis of their functional roles, but no computational methods have been developed to explicitly report a specific variation value in IP efficiencies conveniently, which may hinder the identification of novel modified RNA sites, particularly those with low abundance or less well-characterized.</p><p><strong>Results: </strong>We develop a comprehensive analytical tool, AEEIP, for estimating the IP efficiency and correcting antibody bias in epitranscriptomics directly, AEEIP employs a mixture model to estimate the proportion of modification-containing RNA fragments from the source of IP data. Validation with both simulated and real data shows that AEEIP successfully estimates antibody bias across different replicates and experimental conditions, and reveals that this bias may obscure the accurate identification of m⁶A sites, leading to false negatives in the quantification of m⁶A-seq data. The proposed method provides reproducible IP efficiency analysis and more robust results for quantifying epitranscriptomics, which is available at: https://github.com/whz991026/AEEIP.</p>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"3742-3752"},"PeriodicalIF":4.1,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12446549/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145111685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pathogenic LDLR Variants (c.103 C>T and c.2416dup) in ligand-binding and cytosolic domains in Saudi familial hypercholesterolemia: Molecular characterization and computational insights.","authors":"Hadiah Bassam Al Mahdi, Noor Ahmad Shaik, Babajan Banaganapalli, Sherif Edris, Rawabi Zahed, Hanan Abdelhalim ElSokary, Hussam Daghistani, Yousef Almoghrabi, Safa Bayashut, Alaa Y Edrees, Abdulrahman Mujalli, Eman Alefishat, Ramu Elango, Zuhier Awan","doi":"10.1016/j.csbj.2025.08.029","DOIUrl":"10.1016/j.csbj.2025.08.029","url":null,"abstract":"<p><p>Familial hypercholesterolemia (FH) results in elevated levels of LDL-C, increasing the risk of developing cardiovascular disease. This study aims to identify genetic causes and examine the connection between genetic variants and the resulting genotype-protein phenotype in Saudi FH patients. Whole-exome sequencing (WES) and Sanger sequencing were employed to detect causative variants in affected Saudi FH families and their healthy relatives. Computational tools, including RNA stability analysis, molecular dynamics simulations, and molecular docking were used to assess the impact of these variants on mRNA stability and protein structure, particularly LDLR-LDLRAP1 interactions. WES identified two pathogenic variants in the LDLR gene in two Saudi FH families: c.103 C>T p.(Gln35Ter) and c.2416dup p.(Val806GlyfsTer11), both absent in healthy relatives and regional databases. The c.103 C>T variant alters the secondary RNA structure of LDLR, potentially affecting its stability and function. The c.2416dupG variant truncates the LDLR cytoplasmic tail, disrupting the NPXY-LDLRAP1 interaction and impairing receptor internalization. Molecular dynamics simulations using Desmond revealed increased structural flexibility and altered interaction dynamics in the LDLR protein due to the c.2416dup variant, suggesting further impacts on the protein's functional integrity. In conclusion, this study identifies rare pathogenic variants c.2416dup and c.103 C>T in <i>LDLR</i> in extended Saudi Arabian families. It demonstrates the integration of bioinformatics methods with sequencing data to characterize and elucidate the pathogenic effects of genetic variants, providing comprehensive insights into the intricate interplay between LDLR genetic variants and their molecular impacts in FH patients.</p>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"3770-3784"},"PeriodicalIF":4.1,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12447921/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145111512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}