Frontiers in bioinformatics最新文献

{"title":"Quantification of muscle fiber malformations using edge detection to investigate chronic muscle pressure ulcers.","authors":"Charlene Z L Ong, N Jannah M Nasir, Roy E Welsch, Lisa Tucker-Kellogg, Jagath C Rajapakse","doi":"10.3389/fbinf.2024.1450146","DOIUrl":"10.3389/fbinf.2024.1450146","url":null,"abstract":"<p><strong>Background: </strong>Microscopy of regenerated tissue shows different morphologies between the healing of acute wounds and chronic wounds. This difference can be seen manually by biologists, but computational methods are needed to automate the characterization of morphology and regenerative quality in regenerated muscle tissue.</p><p><strong>Results: </strong>From the detected edge segments, we computed several imaging biomarkers of interest, such as median tortuosity, number of edge segments normalized by area, median edge segment distance and interquartile range of orientation angles of edge segments of the microscope images of successful and unsuccessful muscle regeneration. We observed that muscle fibers in saline-treated pressure ulcers had a larger interquartile range of orientation angles of the edge segments (p = 0.05) and shorter edge segment distances (p = 0.003) compared to those of acute cardiotoxin injuries.</p><p><strong>Conclusion: </strong>Our edge detection method was able to identify statistically significant differences in some of the imaging biomarkers between saline-treated pressure ulcers and cardiotoxin injuries, suggesting that chronic pressure ulcers have increased muscle fiber malformations compared to cardiotoxin injuries.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"4 ","pages":"1450146"},"PeriodicalIF":2.8,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11532102/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577383","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":"DCMA: faster protein backbone dihedral angle prediction using a dilated convolutional attention-based neural network.","authors":"Buzhong Zhang, Meili Zheng, Yuzhou Zhang, Lijun Quan","doi":"10.3389/fbinf.2024.1477909","DOIUrl":"10.3389/fbinf.2024.1477909","url":null,"abstract":"<p><p>The dihedral angle of the protein backbone can describe the main structure of the protein, which is of great significance for determining the protein structure. Many computational methods have been proposed to predict this critically important protein structure, including deep learning. However, these heavyweight methods require more computational resources, and the training time becomes intolerable. In this article, we introduce a novel lightweight method, named dilated convolution and multi-head attention (DCMA), that predicts protein backbone torsion dihedral angles <math><mrow><mo>(</mo> <mrow><mi>ϕ</mi> <mo>,</mo> <mi>ψ</mi></mrow> <mo>)</mo></mrow> </math> . DCMA is stacked by five layers of two hybrid inception blocks and one multi-head attention block (I2A1) module. The hybrid inception blocks consisting of multi-scale convolutional neural networks and dilated convolutional neural networks are designed for capturing local and long-range sequence-based features. The multi-head attention block supplementally strengthens this operation. The proposed DCMA is validated on public critical assessment of protein structure prediction (CASP) benchmark datasets. Experimental results show that DCMA obtains better or comparable generalization performance. Compared to best-so-far methods, which are mostly ensemble models and constructed of recurrent neural networks, DCMA is an individual model that is more lightweight and has a shorter training time. The proposed model could be applied as an alternative method for predicting other protein structural features.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"4 ","pages":"1477909"},"PeriodicalIF":2.8,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11527783/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142570495","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 identification and characterization of chitinase 1 and chitinase 2 from neotropical isolates of <i>Beauveria bassiana</i>.","authors":"Juan Segura-Vega, Allan González-Herrera, Ramón Molina-Bravo, Stefany Solano-González","doi":"10.3389/fbinf.2024.1434442","DOIUrl":"10.3389/fbinf.2024.1434442","url":null,"abstract":"<p><strong>Background: </strong>The fungus <i>Beauveria bassiana</i> is widely used for agronomical applications, mainly in biological control. <i>B. bassiana</i> uses chitinase enzymes to degrade chitin, a major chemical component found in insect exoskeletons and fungal cell walls. However, until recently, genomic information on neotropical isolates, as well as their metabolic and biotechnological potential, has been limited.</p><p><strong>Methods: </strong>Eight complete <i>B. bassiana</i> genomes of Neotropical origin and three references were studied to identify chitinase genes and its corresponding proteins, which were curated and characterized using manual curation and computational tools. We conducted a computational study to highlight functional differences and similarities for chitinase proteins in these Neotropical isolates.</p><p><strong>Results: </strong>Eleven chitinase 1 genes were identified, categorized as chitinase 1.1 and chitinase 1.2. Five chitinase 2 genes were identified but presented a higher sequence conservation across all sequences. Interestingly, physicochemical parameters were more similar between chitinase 1.1 and chitinase 2 than between chitinase 1.1 and 1.2.</p><p><strong>Conclusion: </strong>Chitinases 1 and 2 demonstrated variations, especially within chitinase 1, which presented a potential paralog. These differences were observed in their physical parameters. Additionally, CHIT2 completely lacks a signal peptide. This implies that CHIT1 might be associated with infection processes, while CHIT2 could be involved in morphogenesis and cellular growth. Therefore, our work highlights the importance of computational studies on local isolates, providing valuable resources for further experimental validation. Intrinsic changes within local species can significantly impact our understanding of complex pathogen-host interactions and offer practical applications, such as biological control.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"4 ","pages":"1434442"},"PeriodicalIF":2.8,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11527780/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142570494","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":"Identification of novel drug targets for <i>Helicobacter pylori</i>: structure-based virtual screening of potential inhibitors against DAH7PS protein involved in the shikimate pathway.","authors":"Narjes Noori Goodarzi, Mahshid Khazani Asforooshani, Behzad Shahbazi, Nayereh Rezaie Rahimi, Farzad Badmasti","doi":"10.3389/fbinf.2024.1482338","DOIUrl":"10.3389/fbinf.2024.1482338","url":null,"abstract":"<p><strong>Background: </strong><i>Helicobacter pylori</i>, a bacterium associated with severe gastrointestinal diseases and malignancies, poses a significant challenge because of its increasing antibiotic resistance rates. This study aimed to identify potential drug targets and inhibitors against <i>H. pylori</i> using a structure-based virtual screening (SBVS) approach.</p><p><strong>Methods: </strong>Core-proteome analysis of 132 <i>H. pylori</i> genomes was performed using the EDGAR database. Essential genes were identified and human and gut microbiota homolog proteins were excluded. The DAH7PS protein involved in the shikimate pathway was selected for the structure-based virtual screening (SBVS) approach. The tertiary structure of the protein was predicted through homology modeling (based on PDB ID: 5UXM). Molecular docking was performed to identify potential inhibitors of DAH7PS among StreptomeDB compounds using the AutoDock Vina tool. Molecular dynamics (MD) simulations assessed the stability of DAH7PS-ligand complexes. The complexes were further evaluated in terms of their binding affinity, Lipinski's Rule of Five, and ADMET properties.</p><p><strong>Results: </strong>A total of 54 novel drug targets with desirable properties were identified. DAH7PS was selected for further investigation, and virtual screening of StreptomeDB compounds yielded 36 high-affinity binding of the ligands. Two small molecules, 6,8-Dihydroxyisocoumarin-3-carboxylic acid and Epicatechin, also showed favorable RO5 and ADMET properties. MD simulations confirmed the stability and reliability of DAH7PS-ligand complexes, indicating their potential as inhibitors.</p><p><strong>Conclusion: </strong>This study identified 54 novel drug targets against <i>H. pylori</i>. The DAH7PS protein as a promising drug target was evaluated using a computer-aided drug design. 6,8-Dihydroxyisocoumarin-3-carboxylic acid and Epicatechin demonstrated desirable properties and stable interactions, highlighting their potential to inhibit DAH7PS as an essential protein. Undoubtedly, more experimental validations are needed to advance these findings into practical therapies for treating drug-resistant <i>H. pylori</i>.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"4 ","pages":"1482338"},"PeriodicalIF":2.8,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11527725/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142570497","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":"Editorial: Women in bioinformatics.","authors":"Irma Martínez-Flores, Constanza Cárdenas Carvajal, Viviana Monje-Galvan","doi":"10.3389/fbinf.2024.1499514","DOIUrl":"https://doi.org/10.3389/fbinf.2024.1499514","url":null,"abstract":"","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"4 ","pages":"1499514"},"PeriodicalIF":2.8,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11494442/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142514118","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":"<i>In silico</i> PCR analysis: a comprehensive bioinformatics tool for enhancing nucleic acid amplification assays.","authors":"Ruslan Kalendar, Alexandr Shevtsov, Zhenis Otarbay, Aisulu Ismailova","doi":"10.3389/fbinf.2024.1464197","DOIUrl":"10.3389/fbinf.2024.1464197","url":null,"abstract":"<p><p>Nucleic acid amplification assays represent a pivotal category of methodologies for targeted sequence detection within contemporary biological research, boasting diverse utility in diagnostics, identification, and DNA sequencing. The foundational principles of these assays have been extrapolated to various simple and intricate nucleic acid amplification technologies. Concurrently, a burgeoning trend toward computational or virtual methodologies is exemplified by <i>in silico</i> PCR analysis. <i>In silico</i> PCR analysis is a valuable and productive adjunctive approach for ensuring primer or probe specificity across a broad spectrum of PCR applications encompassing gene discovery through homology analysis, molecular diagnostics, DNA profiling, and repeat sequence identification. The prediction of primer and probe sensitivity and specificity necessitates thorough database searches, accounting for an optimal balance of mismatch tolerance, sequence similarity, and thermal stability. This software facilitates <i>in silico</i> PCR analyses of both linear and circular DNA templates, including bisulfited treatment DNA, enabling multiple primer or probe searches within databases of varying scales alongside advanced search functionalities. This tool is suitable for processing batch files and is essential for automation when working with large amounts of data.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"4 ","pages":"1464197"},"PeriodicalIF":2.8,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11491563/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142485996","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":"Discovery of plasma biomarkers related to blood-brain barrier dysregulation in Alzheimer's disease.","authors":"Yuet Ruh Dan, Keng-Hwee Chiam","doi":"10.3389/fbinf.2024.1463001","DOIUrl":"10.3389/fbinf.2024.1463001","url":null,"abstract":"<p><strong>Introduction: </strong>Blood-based biomarkers are quantitative, non-invasive diagnostic tools. This study aimed to identify candidate biomarkers for Alzheimer's disease (AD) using publicly available omics datasets, using the hypothesis that with blood-brain barrier dysfunction in AD, brain-synthesized proteins can leak into plasma for detection.</p><p><strong>Methods: </strong>Differential abundance results of plasma and brain proteomic datasets were integrated to obtain a list of potential biomarkers. Biological validity was investigated with intercellular communication and gene regulatory analyses on brain single-cell transcriptomics data.</p><p><strong>Results: </strong>Five proteins (APOD, B2M, CFH, CLU, and C3) fit biomarker criteria. 4 corresponding transcripts (APOD, B2M, CLU, and C3) were overexpressed in AD astrocytes, mediated by AD-related dysregulations in transcription factors regulating neuroinflammation. Additionally, CLU specifically induced downstream expression of neuronal death genes.</p><p><strong>Discussion: </strong>In conclusion, a 5-protein panel is shown to effectively identify AD patients, with evidence of disease specificity and biological validity. Future research should investigate the mechanism of protein leakage through the blood-brain barrier.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"4 ","pages":"1463001"},"PeriodicalIF":2.8,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11487119/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142482320","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":"A time-calibrated phylogeny of the diversification of Holoadeninae frogs.","authors":"Júlio C M Chaves, Fábio Hepp, Carlos G Schrago, Beatriz Mello","doi":"10.3389/fbinf.2024.1441373","DOIUrl":"https://doi.org/10.3389/fbinf.2024.1441373","url":null,"abstract":"<p><p>The phylogeny of the major lineages of Amphibia has received significant attention in recent years, although evolutionary relationships within families remain largely neglected. One such overlooked group is the subfamily Holoadeninae, comprising 73 species across nine genera and characterized by a disjunct geographical distribution. The lack of a fossil record for this subfamily hampers the formulation of a comprehensive evolutionary hypothesis for their diversification. Aiming to fill this gap, we inferred the phylogenetic relationships and divergence times for Holoadeninae using molecular data and calibration information derived from the fossil record of Neobatrachia. Our inferred phylogeny confirmed most genus-level associations, and molecular dating analysis placed the origin of Holoadeninae in the Eocene, with subsequent splits also occurring during this period. The climatic and geological events that occurred during the Oligocene-Miocene transition were crucial to the dynamic biogeographical history of the subfamily. However, the wide highest posterior density intervals in our divergence time estimates are primarily attributed to the absence of Holoadeninae fossil information and, secondarily, to the limited number of sampled nucleotide sites.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"4 ","pages":"1441373"},"PeriodicalIF":2.8,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11480671/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142482319","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":"SciJava Ops: an improved algorithms framework for Fiji and beyond.","authors":"Gabriel J Selzer, Curtis T Rueden, Mark C Hiner, Edward L Evans, David Kolb, Marcel Wiedenmann, Christian Birkhold, Tim-Oliver Buchholz, Stefan Helfrich, Brian Northan, Alison Walter, Johannes Schindelin, Tobias Pietzsch, Stephan Saalfeld, Michael R Berthold, Kevin W Eliceiri","doi":"10.3389/fbinf.2024.1435733","DOIUrl":"https://doi.org/10.3389/fbinf.2024.1435733","url":null,"abstract":"<p><p>Decades of iteration on scientific imaging hardware and software has yielded an explosion in not only the size, complexity, and heterogeneity of image datasets but also in the tooling used to analyze this data. This wealth of image analysis tools, spanning different programming languages, frameworks, and data structures, is itself a problem for data analysts who must adapt to new technologies and integrate established routines to solve increasingly complex problems. While many \"bridge\" layers exist to unify pairs of popular tools, there exists a need for a general solution to unify new and existing toolkits. The SciJava Ops library presented here addresses this need through two novel principles. Algorithm implementations are declared as plugins called Ops, providing a uniform interface regardless of the toolkit they came from. Users express their needs declaratively to the Op environment, which can then find and adapt available Ops on demand. By using these principles instead of direct function calls, users can write streamlined workflows while avoiding the translation boilerplate of bridge layers. Developers can easily extend SciJava Ops to introduce new libraries and more efficient, specialized algorithm implementations, even immediately benefitting existing workflows. We provide several use cases showing both user and developer benefits, as well as benchmarking data to quantify the negligible impact on overall analysis performance. We have initially deployed SciJava Ops on the Fiji platform, however it would be suitable for integration with additional analysis platforms in the future.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"4 ","pages":"1435733"},"PeriodicalIF":2.8,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11466933/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142482321","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":"Pangenome comparison via ED strings.","authors":"Esteban Gabory, Moses Njagi Mwaniki, Nadia Pisanti, Solon P Pissis, Jakub Radoszewski, Michelle Sweering, Wiktor Zuba","doi":"10.3389/fbinf.2024.1397036","DOIUrl":"10.3389/fbinf.2024.1397036","url":null,"abstract":"<p><strong>Introduction: </strong>An elastic-degenerate (ED) string is a sequence of sets of strings. It can also be seen as a directed acyclic graph whose edges are labeled by strings. The notion of ED strings was introduced as a simple alternative to variation and sequence graphs for representing a pangenome, that is, a collection of genomic sequences to be analyzed jointly or to be used as a reference.</p><p><strong>Methods: </strong>In this study, we define notions of <i>matching statistics</i> of two ED strings as similarity measures between pangenomes and, consequently infer a corresponding distance measure. We then show that both measures can be computed efficiently, in both theory and practice, by employing the <i>intersection graph</i> of two ED strings.</p><p><strong>Results: </strong>We also implemented our methods as a software tool for pangenome comparison and evaluated their efficiency and effectiveness using both synthetic and real datasets.</p><p><strong>Discussion: </strong>As for efficiency, we compare the runtime of the intersection graph method against the classic product automaton construction showing that the intersection graph is faster by up to one order of magnitude. For showing effectiveness, we used real SARS-CoV-2 datasets and our matching statistics similarity measure to reproduce a well-established clade classification of SARS-CoV-2, thus demonstrating that the classification obtained by our method is in accordance with the existing one.</p>","PeriodicalId":73066,"journal":{"name":"Frontiers in bioinformatics","volume":"4 ","pages":"1397036"},"PeriodicalIF":2.8,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11464492/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142402117","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}