Evolutionary Bioinformatics最新文献

{"title":"Comparative Phylogenetic Analysis and Protein Prediction Reveal the Taxonomy and Diverse Distribution of Virulence Factors in Foodborne <i>Clostridium</i> Strains.","authors":"Ming Zhang, Zhenzhen Yin","doi":"10.1177/11769343241294153","DOIUrl":"10.1177/11769343241294153","url":null,"abstract":"<p><strong>Background: </strong><i>Clostridium botulinum</i> and <i>Clostridium perfringens</i>, 2 major foodborne pathogenic fusobacteria, have a variety of virulent protein types with nervous and enterotoxic pathogenic potential, respectively.</p><p><strong>Objective: </strong>The relationship between the molecular evolution of the 2 <i>Clostridium</i> genomes and virulence proteins was studied via a bioinformatics prediction method. The genetic stability, main features of gene coding and structural characteristics of virulence proteins were compared and analyzed to reveal the phylogenetic characteristics, diversity, and distribution of virulence factors of foodborne <i>Clostridium</i> strains.</p><p><strong>Methods: </strong>The phylogenetic analysis was performed via composition vector and average nucleotide identity based methods. Evolutionary distances of virulence genes relative to those of housekeeping genes were calculated via multilocus sequence analysis. Bioinformatics software and tools were used to predict and compare the main functional features of genes encoding virulence proteins, and the structures of virulence proteins were predicted and analyzed through homology modeling and a deep learning algorithm.</p><p><strong>Results: </strong>According to the diversity of toxins, genome evolution tended to cluster based on the protein-coding virulence genes. The evolutionary transfer distances of virulence genes relative to those of housekeeping genes in <i>C. botulinum</i> strains were greater than those in <i>C. perfringens</i> strains, and BoNTs and alpha toxin proteins were located extracellularly. The BoNTs have highly similar structures, but BoNT/A/B and BoNT/E/F have significantly different conformations. The beta2 toxin monomer structure is similar to but simpler than the alpha toxin monomer structure, which has 2 mobile loops in the N-terminal domain. The C-terminal domain of the CPE trimer forms a \"claudin-binding pocket\" shape, which suggests biological relevance, such as in pore formation.</p><p><strong>Conclusions: </strong>According to the genotype of protein-coding virulence genes, the evolution of <i>Clostridium</i> showed a clustering trend. The genetic stability, functional and structural characteristics of foodborne <i>Clostridium</i> virulence proteins reveal the taxonomy and diverse distribution of virulence factors.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11536399/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142583424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Effective Computational Method for Predicting Self-Interacting Proteins Based on VGGNet Convolutional Neural Network and Gray-Level Co-occurrence Matrix.","authors":"Dan-Hua Chu, Ji-Yong An, Xiao-Mei Nie","doi":"10.1177/11769343241292224","DOIUrl":"10.1177/11769343241292224","url":null,"abstract":"<p><strong>Introduction: </strong>Predicting Self-interacting proteins (SIPs) is a crucial area of research in predicting protein functions, as well as in understanding gene-disease and disease-drug associations. These interactions are integral to numerous cellular processes and play pivotal roles within cells. However, traditional methods for identifying SIPs through biological experiments are often expensive, time-consuming, and have long cycles. Therefore, the development of effective computational methods for accurately predicting SIPs is not only necessary but also presents a significant challenge.</p><p><strong>Results: </strong>In this research, we introduce a novel computational prediction technique, VGGNGLCM, which leverages protein sequence data. This method integrates the VGGNet deep convolutional neural network (VGGN) with the Gray-Level Co-occurrence Matrix (GLCM) to detect Self-interacting proteins associations. Specifically, we initially utilized Position Specific Scoring Matrix (PSSM) to capture protein evolutionary information and integrated key features from PSSM using GLCM. We then employed VGGNet as a predictive classifier, leveraging its capabilities for powerful learning and classification prediction. Subsequently, the extracted features were input into the VGGNet deep convolutional neural network to identify Self-interacting proteins. To evaluate the performance of the VGGNGLCM model, we conducted experiments using yeast and human datasets, achieving average accuracies of 95.68% and 97.72% respectively. Additionally, we compared the prediction performance of the VGGNet classifier with that of the Convolutional Neural Network (CNN) and the state-of-the-art Support Vector Machine (SVM) using the same feature extraction method. We also compared the prediction ability of VGGNGLCM with other existing approaches. The comparison results further demonstrate the superior performance of VGGNGLCM over other prediction models in this domain.</p><p><strong>Conclusion: </strong>The experimental verification further strengthens the evidence that VGGNGLCM is effective and robust compared to existing methods. It also highlights the high accuracy and robustness of the VGGNGLCM model in predicting Self-interacting proteins (SIPs). Consequently, we believe that the VGGNGLCM method serves as a valuable computational tool and can catalyze extensive bioinformatics research related to SIPs prediction.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11503870/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142512188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comprehensive Profiling of Transcriptome and m6A Epitranscriptome Uncovers the Neurotoxic Effects of Yunaconitine on HT22 Cells.","authors":"Beian Lin, Jian Zhang, Mengting Chen, Xinyue Gao, Jiaxin Wen, Kun Tian, Yajiao Wu, Zekai Chen, Qiaomei Yang, An Zhu, Chunhong Du","doi":"10.1177/11769343241290461","DOIUrl":"10.1177/11769343241290461","url":null,"abstract":"<p><strong>Objective: </strong>To explore different mRNA transcriptome patterns and RNA N6-methyladenosine (m6A) alteration in yunaconitine (YA)-treated HT22 mouse hippocampal neuron, and uncover the role of abnormal mRNA expression and RNA m6A modification in YA-induced neurotoxicity.</p><p><strong>Methods: </strong>HT22 cells were treated with 0, 5, 10, and 50 μM of YA for 72 h to evaluate their viability and GSH content. Subsequently, mRNA-seq and MeRIP-seq analyses were performed on HT22 cells treated with 0 and 10 μM YA for 72 h, and molecular docking was used to simulate interactions between YA and differentially expressed m6A regulators. The mitochondrial membrane potential was examined using the JC-10 probe, and RT-qPCR was conducted to verify the expression levels of differentially expressed m6A regulatory factors, as well as to assess alterations in the mRNA expression levels of antioxidant genes.</p><p><strong>Results: </strong>YA treatment significantly reduced the viability of HT22 cells and decreased GSH content. The mRNA-seq analysis obtained 1018 differentially expressed genes, KEGG and GO enrichment results of differentially expressed genes mainly comprise the nervous system development, cholinergic synapse, response to oxidative stress, and mitochondrial inner membrane. A total of 7 differentially expressed m6A regulators were identified by MeRIP-seq. Notably, molecular docking results suggested a stable interaction between YA and most of the differentially expressed m6A regulators.</p><p><strong>Conclusion: </strong>This study showed that YA-induced HT22 cell damage was associated with the increased methylation modification level of target gene m6A and abnormal expression of m6A regulators.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11526304/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142559292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Label Transfer for Drug Disease Association in Three Meta-Paths","authors":"Nam Anh Dao, Manh Hung Le, Xuan Tho Dang","doi":"10.1177/11769343241272414","DOIUrl":"https://doi.org/10.1177/11769343241272414","url":null,"abstract":"The identification of potential interactions and relationships between diseases and drugs is significant in public health care and drug discovery. As we all know, experimenting to determine the drug-disease interactions is very expensive in both time and money. However, there are still many drug-disease associations that are still undiscovered and potential. Therefore, the development of computational methods to explore the relationship between drugs and diseases is very important and essential. Many computational methods for predicting drug-disease associations have been developed based on known interactions to learn potential interactions of unknown drug-disease pairs. In this paper, we propose 3 new main groups of meta-paths based on the heterogeneous biological network of drug-protein-disease objects. For each meta-path, we design a machine learning model, then an integrated learning method is formed by these models. We evaluated our approach on 3 standard datasets which are DrugBank, OMIM, and Gottlieb’s dataset. Experimental results demonstrate that the proposed method is better than some recent methods such as EMP-SVD, LRSSL, MBiRW, MPG-DDA, SCMFDD,. . . in some measures such as AUC, AUPR, and F1-score.","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recombination Events Among SARS-CoV-2 Omicron Subvariants: Impact on Spike Interaction With ACE2 Receptor and Neutralizing Antibodies.","authors":"Marwa Arbi, Marwa Khedhiri, Kaouther Ayouni, Oussema Souiai, Samar Dhouib, Nidhal Ghanmi, Alia Benkahla, Henda Triki, Sondes Haddad-Boubaker","doi":"10.1177/11769343241272415","DOIUrl":"10.1177/11769343241272415","url":null,"abstract":"<p><p>The recombination plays a key role in promoting evolution of RNA viruses and emergence of potentially epidemic variants. Some studies investigated the recombination occurrence among SARS-CoV-2, without exploring its impact on virus-host interaction. In the aim to investigate the burden of recombination in terms of frequency and distribution, the occurrence of recombination was first explored in 44 230 Omicron sequences among BQ subvariants and the under investigation \"ML\" (Multiple Lineages) denoted sequences, using 3seq software. Second, the recombination impact on interaction between the Spike protein and ACE2 receptor as well as neutralizing antibodies (nAbs), was analyzed using docking tools. Recombination was detected in 56.91% and 82.20% of BQ and ML strains, respectively. It took place mainly in spike and ORF1a genes. For BQ recombinant strains, the docking analysis showed that the spike interacted strongly with ACE2 and weakly with nAbs. The mutations S373P, S375F and T376A constitute a residue network that enhances the RBD interaction with ACE2. Thirteen mutations in RBD (S373P, S375F, T376A, D405N, R408S, K417N, N440K, S477N, P494S, Q498R, N501Y, and Y505H) and NTD (Y240H) seem to be implicated in immune evasion of recombinants by altering spike interaction with nAbs. In conclusion, this \"in silico\" study demonstrated that the recombination mechanism is frequent among Omicron BQ and ML variants. It highlights new key mutations, that potentially implicated in enhancement of spike binding to ACE2 (F376A) and escape from nAbs (RBD: F376A, D405N, R408S, N440K, S477N, P494S, and Y505H; NTD: Y240H). Our findings present considerable insights for the elaboration of effective prophylaxis and therapeutic strategies against future SARS-CoV-2 waves.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11325312/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141989369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single-cell RNA Sequencing Identifies Natural Kill Cell-Related Transcription Factors Associated With Age-Related Macular Degeneration.","authors":"Yili Luo, Jianpeng Liu, Wangqiang Feng, Da Lin, Mengji Chen, Haihua Zheng","doi":"10.1177/11769343241272413","DOIUrl":"10.1177/11769343241272413","url":null,"abstract":"<p><strong>Background: </strong>Age-related Macular Degeneration (AMD) poses a growing global health concern as the leading cause of central vision loss in elderly people.</p><p><strong>Objection: </strong>This study focuses on unraveling the intricate involvement of Natural Killer (NK) cells in AMD, shedding light on their immune responses and cytokine regulatory roles.</p><p><strong>Methods: </strong>Transcriptomic data from the Gene Expression Omnibus database were utilized, employing single-cell RNA-seq analysis. High-dimensional weighted gene co-expression network analysis (hdWGCNA) and single-cell regulatory network inference and clustering (SCENIC) analysis were applied to reveal the regulatory mechanisms of NK cells in early-stage AMD patients. Machine learning models, such as random forests and decision trees, were employed to screen hub genes and key transcription factors (TFs) associated with AMD.</p><p><strong>Results: </strong>Distinct cell clusters were identified in the present study, especially the T/NK cluster, with a notable increase in NK cell abundance observed in AMD. Cell-cell communication analyses revealed altered interactions, particularly in NK cells, indicating their potential role in AMD pathogenesis. HdWGCNA highlighted the turquoise module, enriched in inflammation-related pathways, as significantly associated with AMD in NK cells. The SCENIC analysis identified key TFs in NK cell regulatory networks. The integration of hub genes and TFs identified <i>CREM, FOXP1, IRF1, NFKB2</i>, and <i>USF2</i> as potential predictors for AMD through machine learning.</p><p><strong>Conclusion: </strong>This comprehensive approach enhances our understanding of NK cell dynamics, signaling alterations, and potential predictive models for AMD. The identified TFs provide new avenues for molecular interventions and highlight the intricate relationship between NK cells and AMD pathogenesis. Overall, this study contributes valuable insights for advancing our understanding and management of AMD.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11325330/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141989370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MicroRNA Transcriptomes Reveal Prevalence of Rare and Species-Specific Arm Switching Events During Zebrafish Ontogenesis.","authors":"Arthur Casulli de Oliveira, Luiz Augusto Bovolenta, Lucas Figueiredo, Amanda De Oliveira Ribeiro, Beatriz Jacinto Alves Pereira, Talita Roberto Aleixo de Almeida, Vinicius Farias Campos, James G Patton, Danillo Pinhal","doi":"10.1177/11769343241263230","DOIUrl":"10.1177/11769343241263230","url":null,"abstract":"<p><p>In metazoans, microRNAs (miRNAs) are essential regulators of gene expression, affecting critical cellular processes from differentiation and proliferation, to homeostasis. During miRNA biogenesis, the miRNA strand that loads onto the RNA-induced Silencing Complex (RISC) can vary, leading to changes in gene targeting and modulation of biological pathways. To investigate the impact of these \"arm switching\" events on gene regulation, we analyzed a diverse range of tissues and developmental stages in zebrafish by comparing 5p and 3p arms accumulation dynamics between embryonic developmental stages, adult tissues, and sexes. We also compared variable arm usage patterns observed in zebrafish to other vertebrates including arm switching data from fish, birds, and mammals. Our comprehensive analysis revealed that variable arm usage events predominantly take place during embryonic development. It is also noteworthy that isomiR occurrence correlates to changes in arm selection evidencing an important role of microRNA distinct isoforms in reinforcing and modifying gene regulation by promoting dynamics switches on miRNA 5p and 3p arms accumulation. Our results shed new light on the emergence and coordination of gene expression regulation and pave the way for future investigations in this field.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11271096/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141762332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Spatio-Temporal Expression Profiles of Silkworm Pseudogenes Provide Valuable Insights into Their Biological Roles.","authors":"Linrong Wan, Siyuan Su, Jinyun Liu, Bangxing Zou, Yaming Jiang, Beibei Jiao, Shaokuan Tang, Youhong Zhang, Cao Deng, Wenfu Xiao","doi":"10.1177/11769343241261814","DOIUrl":"10.1177/11769343241261814","url":null,"abstract":"<p><strong>Background: </strong>Pseudogenes are sequences that have lost the ability to transcribe RNA molecules or encode truncated but possibly functional proteins. While they were once considered to be meaningless remnants of evolution, recent researches have shown that pseudogenes play important roles in various biological processes. However, the studies of pseudogenes in the silkworm, an important model organism, are limited and have focused on single or only a few specific genes.</p><p><strong>Objective: </strong>To fill these gaps, we present a systematic genome-wide studies of pseudogenes in the silkworm.</p><p><strong>Methods: </strong>We identified the pseudogenes in the silkworm using the silkworm genome assemblies, transcriptome, protein sequences from silkworm and its related species. Then we used transcriptome datasets from 832 RNA-seq analyses to construct spatio-temporal expression profiles for these pseudogenes. Additionally, we identified tissue-specifically expressed and differentially expressed pseudogenes to further understand their characteristics. Finally, the functional roles of pseudogenes as lncRNAs were systematically analyzed.</p><p><strong>Results: </strong>We identified a total of 4410 pseudogenes, which were grouped into 4 groups, including duplications (DUPs), unitary pseudogenes (Unitary), processed pseudogenes (retropseudogenes, RETs), and fragments (FRAGs). The most of pseudogenes in the domestic silkworm were generated before the divergence of wild and domestic silkworm, however, the domestication may also involve in the accumulation of pseudogenes. These pseudogenes were clearly divided into 2 cluster, a highly expressed and a lowly expressed, and the posterior silk gland was the tissue with the most tissue-specific pseudogenes (199), implying these pseudogenes may be involved in the development and function of silkgland. We identified 3299 lncRNAs in these pseudogenes, and the target genes of these lncRNAs in silkworm pseudogenes were enriched in the egg formation and olfactory function.</p><p><strong>Conclusions: </strong>This study replenishes the genome annotations for silkworm, provide valuable insights into the biological roles of pseudogenes. It will also contribute to our understanding of the complex gene regulatory networks in the silkworm and will potentially have implications for other organisms as well.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11179516/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141332419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on Allele Specific Expression of Long-Term Residents in High Altitude Areas","authors":"Chao He, Bin Zhu, Wenwen Gao, Qianjin Wu, Changshui Zhang","doi":"10.1177/11769343241257344","DOIUrl":"https://doi.org/10.1177/11769343241257344","url":null,"abstract":"In diploid organisms, half of the chromosomes in each cell come from the father and half from the mother. Through previous studies, it was found that the paternal chromosome and the maternal chromosome can be regulated and expressed independently, leading to the emergence of allele specific expression (ASE). In this study, we analyzed the differential expression of alleles in the high-altitude population and the normal population based on the RNA sequencing data. Through gene cluster analysis and protein interaction network analysis, we found some changes occurred at the gene level, and some negative effects. During the study, we realized that the calmodulin homology domain may have a certain correlation with long-term survival at high altitude. The plateau environment is characterized by hypoxia, low air pressure, strong ultraviolet radiation, and low temperature. Accordingly, the genetic changes in the process of adaptation are mainly reflected in these characteristics. High altitude generation living is also highly related to cancer, immune disease, cardiovascular disease, neurological disease, endocrine disease, and other diseases. Therefore, the medical system in high altitude areas should pay more attention to these diseases.","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141190451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Integrated Framework for Analysis and Prediction of Impact of Single Nucleotide Polymorphism Associated with Human Diseases.","authors":"Syed Shah Muhammad, Muhammad Shoaib, Muhammad Tariq Pervez","doi":"10.1177/11769343241249916","DOIUrl":"10.1177/11769343241249916","url":null,"abstract":"<p><p>Single nucleotide polymorphisms are most common type of genetic variation in human genome. Analyzing genetic variants can help us better understand the genetic basis of diseases and develop predictive models which are useful to identify individuals who are at increased risk for certain diseases. Several SNP analysis tools have already been developed. For running these tools, the user needs to collect data from various databases. Secondly, often researchers have to use multiple variant analysis tools for cross validating their results and increase confidence in their findings. Extracting data from multiple databases and running multiple tools at a time, increases complexity and time required for analysis. There are some web-based tools that integrate multiple genetic variant databases and provide variant annotations for a few tools. These approaches have some limitations such as retrieving annotation information, filtering common pathogenic variants. The proposed web-based tool, namely IPSNP: An Integrated Platform for Predicting Impact of SNPs is written in Django which is a python-based framework. It uses RESTful API of MyVariant.info to extract annotation information of variants associated with a given gene, rsID, HGVS format variants specified in a VCF file for 29 tools. The results are in the form of a CSV file of predictions (1) derived from the consensus decision, (2) a file having annotations for the variants associated with the given gene, (3) a file showing variants declared as pathogenic commonly by the selected tools, and (4) a CSV file containing chromosome coordinates based on GRCh37 and GRCh38 genome assemblies, rsIDs and proteomic data, so that users may use tools of their choice and avoiding manual parameter collection for each tool. IPSNP is a valuable resource for researchers and clinicians and it can help to save time and effort in discovering the novel disease-associated variants and the development of personalized treatments.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11088291/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140913243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}