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PubMed2025

VirDetector: a bioinformatic pipeline for virus surveillance using nanopore sequencing.

SUMMARY: Virus surveillance programmes are designed to counter the growing threat of viral outbreaks to human health. Nanopore sequencing, in particular, has proven to be suitable for this purpose, as it is readily available and provides rapid results. However, as special bioinformatic programs are required to extract the relevant information from the sequencing data, applications are needed that allow users without extensive bioinformatics knowledge to carry out the relevant analysis steps. We present VirDetector, a bioinformatic pipeline for virus surveillance using nanopore sequencing. The pipeline automatically installs all required programs and databases and allows all its steps to be executed with a single console command. After preprocessing the samples, including the possibility for basecalling, the pipeline classifies each sample taxonomically and reconstructs the viral consensus genomes, which are then used in phylogenetic analyses. This streamlined workflow provides a user-friendly and efficient solution for monitoring viral pathogens. AVAILABILITY AND IMPLEMENTATION: VirDetector is freely available at https://github.com/NLKaiser/VirDetector and https://zenodo.org/records/14637302 (10.5281/zenodo.14637302).

Nanopore Sequencing↗

PubMed2001

Detecting gene relations from Medline abstracts.

Research in bioinformatics in the past decade has generated a large volume of textual biological data stored in databases such as MEDLINE. It takes a copious amount of effort and time, even for expert users, to manually extract useful information embedded in such a large volume of retrieved data and automated intelligent text analysis tools are increasingly becoming essential. In this article, we present a simple analysis and knowledge discovery method that can identify related genes as well as their shared functionality (if any) based on a collection of relevant retrieved relevant MEDLINE documents. The relative computational simplicity of the proposed method makes it possible to process and analyze large volumes of data in a short time. Hence, it significantly contributes to and enhances a user's ability to discover such embedded information. Two case studies are presented that indicate the usefulness of the proposed method.

Abstracting and Indexing↗

PubMed2005

Use of endogenous retroviral sequences (ERVs) and structural markers for retroviral phylogenetic inference and taxonomy.

BACKGROUND: Endogenous retroviral sequences (ERVs) are integral parts of most eukaryotic genomes and vastly outnumber exogenous retroviruses (XRVs). ERVs with a relatively complete structure were retrieved from the genetic archives of humans and chickens, diametrically opposite representatives of vertebrate retroviruses (over 3300 proviruses), and analyzed, using a bioinformatic program, RetroTector, developed by us. This rich source of proviral information, accumulated in a local database, and a collection of XRV sequences from the literature, allowed the reconstruction of a Pol based phylogenetic tree, more extensive than previously possible. The aim was to find traits useful for classification and evolutionary studies of retroviruses. Some of these traits have been used by others, but they are here tested in a wider context than before. RESULTS: In the ERV collection we found sequences similar to the XRV-based genera: alpha-, beta-, gamma-, epsilon- and spumaretroviruses. However, the occurrence of intermediates between them indicated an evolutionary continuum and suggested that taxonomic changes eventually will be necessary. No delta or lentivirus representatives were found among ERVs. Classification based on Pol similarity is congruent with a number of structural traits. Acquisition of dUTPase occurred three times in retroviral evolution. Loss of one or two NC zinc fingers appears to have occurred several times during evolution. Nucleotide biases have been described earlier for lenti-, delta- and betaretroviruses and were here confirmed in a larger context. CONCLUSION: Pol similarities and other structural traits contribute to a better understanding of retroviral phylogeny. "Global" genomic properties useful in phylogenies are i.) translational strategy, ii.) number of Gag NC zinc finger motifs, iii.) presence of Pro N-terminal dUTPase (dUTPasePro), iv.) presence of Pro C-terminal G-patch and v.) presence of a GPY/F motif in the Pol integrase (IN) C-terminal domain. "Local" retroviral genomic properties useful for delineation of lower level taxa are i.) host species range, ii.) nucleotide compositional bias and iii.) LTR lengths.

Endogenous Retroviruses↗

PubMed2006

Bioinformatics and multiepitope DNA immunization to design rational snake antivenom.

BACKGROUND: Snake venom is a potentially lethal and complex mixture of hundreds of functionally diverse proteins that are difficult to purify and hence difficult to characterize. These difficulties have inhibited the development of toxin-targeted therapy, and conventional antivenom is still generated from the sera of horses or sheep immunized with whole venom. Although life-saving, antivenoms contain an immunoglobulin pool of unknown antigen specificity and known redundancy, which necessitates the delivery of large volumes of heterologous immunoglobulin to the envenomed victim, thus increasing the risk of anaphylactoid and serum sickness adverse effects. Here we exploit recent molecular sequence analysis and DNA immunization tools to design more rational toxin-targeted antivenom. METHODS AND FINDINGS: We developed a novel bioinformatic strategy that identified sequences encoding immunogenic and structurally significant epitopes from an expressed sequence tag database of a venom gland cDNA library of Echis ocellatus, the most medically important viper in Africa. Focusing upon snake venom metalloproteinases (SVMPs) that are responsible for the severe and frequently lethal hemorrhage in envenomed victims, we identified seven epitopes that we predicted would be represented in all isomers of this multimeric toxin and that we engineered into a single synthetic multiepitope DNA immunogen (epitope string). We compared the specificity and toxin-neutralizing efficacy of antiserum raised against the string to antisera raised against a single SVMP toxin (or domains) or antiserum raised by conventional (whole venom) immunization protocols. The SVMP string antiserum, as predicted in silico, contained antibody specificities to numerous SVMPs in E. ocellatus venom and venoms of several other African vipers. More significantly, the antiserum cross-specifically neutralized hemorrhage induced by E. ocellatus and Cerastes cerastes cerastes venoms. CONCLUSIONS: These data provide valuable sequence and structure/function information of viper venom hemorrhagins but, more importantly, a new opportunity to design toxin-specific antivenoms-the first major conceptual change in antivenom design after more than a century of production. Furthermore, this approach may be adapted to immunotherapy design in other cases where targets are numerous, diverse, and poorly characterized such as those generated by hypermutation or antigenic variation.

Amino Acid Sequence↗

PubMed2026

Pithos - a scalable and secure data container for FAIR-compliant research data management in life sciences.

Modern research techniques have led to exponential growth in the volume and complexity of scientific data. Consequently, managing these volumes securely and efficiently has become a major challenge. While all research domains face these challenges, life science research is particularly affected because current approaches often rely on a large set of different file formats, with metadata stored in separated databases or spreadsheets. This leads to fragmented datasets, orphaned data, and compromised research reproducibility. Traditional solutions also force researchers to choose between security and accessibility, with encrypted files preventing selective access and indexed formats lacking adequate security for sensitive data. These limitations are particularly problematic in large-scale genomic studies where researchers must decompress multi-gigabyte files to access specific regions, creating computational bottlenecks and inefficient network usage when working with cloud-stored datasets. We introduce Pithos, a next-generation file format specifically designed for scientific data management in distributed cloud environments. The format uses content-defined chunking to enable efficient deduplication across distributed storage systems, thereby reducing storage costs and bandwidth requirements. The append-only structure ensures data immutability and allows for incremental updates without compromising content. Benchmark results show that Pithos outperforms existing solutions in read and write performance, with comparable or improved storage efficiency.

Biological Science Disciplines↗

PubMed2026

Genetic insights into lung squamous cell carcinoma: how TP53 and CSMD3 co-mutations shape prognosis and immune response.

BACKGROUND: Lung squamous cell carcinoma (LUSC) accounts for a significant proportion of lung cancer cases and is often associated with smoking and various environmental factors. The prognostic and immunologic implications of TP53 and CSMD3 co-mutations in LUSC remain poorly understood. This study aimed to investigate the role of TP53/CSMD3 co-mutations in LUSC using comprehensive bioinformatics analyses. METHODS: Data from 487 LUSC patients were obtained from The Cancer Genome Atlas (TCGA) database, with external validation performed using the combined cohort. Patients were stratified into TP53/CSMD3 co-mutation, single-mutation, and wild-type (WT) groups. Prognostic analysis was conducted using Kaplan-Meier survival curves. Tumor mutational burden (TMB) was calculated, and immune cell infiltration was assessed using multiple algorithms. Differentially expressed genes (DEGs) between co-mutated and WT groups were identified, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. A nomogram incorporating mutation status, gender, age, and tumor stage (T stage) was developed for individualized prognostic prediction. RESULTS: The TP53/CSMD3 co-mutated group exhibited significantly better overall survival (OS) compared to single-mutation and WT groups. TMB scores were markedly higher in co-mutated patients, suggesting potential sensitivity to immune checkpoint inhibitors. Immune infiltration analysis revealed distinct profiles, including elevated CD8 T cells and reduced immunosuppressive components, in the co-mutation group. A total of 403 DEGs were identified between co-mutated and WT groups, with significant enrichment in immune-related pathways. Mechanistically, the co-mutation was associated with distinct downregulation of complement negative regulators (CFH/CFI), indicating complement hyperactivation independent of TMB. The constructed nomogram provided accurate individualized prognostic assessments. CONCLUSIONS: The co-mutation of TP53 and CSMD3 identifies a distinct LUSC subtype with favorable survival, marked by high TMB and an immune-activated microenvironment. Beyond TMB-driven neoantigen generation, the significant downregulation of complement negative regulators (CFH/CFI) reveals an independent complement hyperactivation pathway associated with CSMD3 loss. The constructed nomogram provides accurate individualized survival prediction. These findings establish TP53/CSMD3 co-mutation as a promising prognostic biomarker and offer mechanistic insights for personalized immunotherapy strategies. Future prospective cohorts are warranted to validate its predictive value.

Lung squamous cell carcinoma (LUSC)↗

PubMed2026

Molecular Characterization of Listeria monocytogenes Isolated from Retail Yak Meat in Nyingchi, Xizang, China.

Listeria monocytogenes is a Gram-positive zoonotic pathogen responsible for listeriosis, a severe foodborne disease with high mortality in humans and animals. This study aimed to investigate the molecular epidemiology and genomic characteristics of L. monocytogenes isolated from raw yak meat in Nyingchi, Xizang, China. A total of 231 yak-related samples were collected in Nyingchi, consisting of 214 retail raw yak meat samples, 14 farm environmental samples, and 3 nearby water source samples. L. monocytogenes isolates were identified and characterized using culture-based methods, PCR serotyping, and whole-genome sequencing (WGS). Bioinformatic analyses were performed for virulence, antimicrobial resistance, and functional gene annotation using KEGG and COG databases. The overall contamination rate of Lm was 13.08% (28/214) for retail raw yak meat samples, whereas no isolates were recovered from 14 farm environmental samples (0.00%, 0/14) and 3 nearby water source samples (0.00%, 0/3). The serotypes of isolates were 1/2a (9/28, 32.14%), 1/2b (7/28, 25.00%), and 1/2c (12/28, 42.86%). These 28 isolates exhibited varied antimicrobial resistance profiles, with universal resistance to trimethoprim-sulfamethoxazole, high resistance to erythromycin and clindamycin, and low resistance to vancomycin. MLST analysis revealed seven sequence types (STs): ST9 (12/28, 42.86%), ST619 (6/28, 21.43%), ST8 (6/28, 21.43%), ST7 (1/28, 3.57%), ST87 (1/28, 3.57%), ST121 (1/28, 3.57%), ST297 (1/28, 3.57%). ST619 isolates harbored multiple virulence genes, including those located on Listeria pathogenicity islands LIPI-1, LIPI-3, and LIPI-4, indicating high genomic potential for virulence. Representative isolate Y2 (ST619) possessed a 3,009,858 bp genome with 3036 coding genes, four genomic islands, and two prophages. Functional annotation revealed enrichment of genes involved in carbohydrate transport and metabolism and amino acid biosynthesis pathways. Our findings provide the first genomic insight into L. monocytogenes contamination in yak meat from Nyingchi, Xizang, China, highlighting the urgent need to strengthen food safety monitoring and hygiene management in this region.

Listeria monocytogenes↗

PubMed2004

[Cloning and expression of a homologue of human macrophage migration inhibitory factor from P. falciparum 3D7].

OBJECTIVE: To clone and express a homologue of human macrophage migration inhibitory factor (MIF) from P. falciparum 3D7--PfMIF. METHODS: The nucleotide sequence of PfMIF was found through blast P. falciparum genomic sequence databases with the amino acid sequence of human MIF (HuMIF). RT-PCR, DNA sequencing, and bioinformatics analysis were used for the cloning of Pfmif gene. The recombinant protein was expressed in E. coli and purified through the affinity column. RESULTS: The full length of Pfmif gene was cloned and sequenced. It was composed of 351 nucleotides and encoded 116 amino acids with the typical characteristic of MIF family. The recombinant protein was successfully expressed and purified. CONCLUSIONS: The Pfmif gene and recombinant protein were successfully isolated and PfMIF was preliminarily identified as a novel member of MIF family.

Amino Acid Sequence↗

PubMed2006

The Gaggle: an open-source software system for integrating bioinformatics software and data sources.

BACKGROUND: Systems biologists work with many kinds of data, from many different sources, using a variety of software tools. Each of these tools typically excels at one type of analysis, such as of microarrays, of metabolic networks and of predicted protein structure. A crucial challenge is to combine the capabilities of these (and other forthcoming) data resources and tools to create a data exploration and analysis environment that does justice to the variety and complexity of systems biology data sets. A solution to this problem should recognize that data types, formats and software in this high throughput age of biology are constantly changing. RESULTS: In this paper we describe the Gaggle -a simple, open-source Java software environment that helps to solve the problem of software and database integration. Guided by the classic software engineering strategy of separation of concerns and a policy of semantic flexibility, it integrates existing popular programs and web resources into a user-friendly, easily-extended environment. We demonstrate that four simple data types (names, matrices, networks, and associative arrays) are sufficient to bring together diverse databases and software. We highlight some capabilities of the Gaggle with an exploration of Helicobacter pylori pathogenesis genes, in which we identify a putative ricin-like protein -a discovery made possible by simultaneous data exploration using a wide range of publicly available data and a variety of popular bioinformatics software tools. CONCLUSION: We have integrated diverse databases (for example, KEGG, BioCyc, String) and software (Cytoscape, DataMatrixViewer, R statistical environment, and TIGR Microarray Expression Viewer). Through this loose coupling of diverse software and databases the Gaggle enables simultaneous exploration of experimental data (mRNA and protein abundance, protein-protein and protein-DNA interactions), functional associations (operon, chromosomal proximity, phylogenetic pattern), metabolic pathways (KEGG) and Pubmed abstracts (STRING web resource), creating an exploratory environment useful to 'web browser and spreadsheet biologists', to statistically savvy computational biologists, and those in between. The Gaggle uses Java RMI and Java Web Start technologies and can be found at http://gaggle.systemsbiology.net.

Computational Biology↗

PubMed2006

Defining the fold space of membrane proteins: the CAMPS database.

Recent progress in structure determination techniques has led to a significant growth in the number of known membrane protein structures, and the first structural genomics projects focusing on membrane proteins have been initiated, warranting an investigation of appropriate bioinformatics strategies for optimal structural target selection for these molecules. What determines a membrane protein fold? How many membrane structures need to be solved to provide sufficient structural coverage of the membrane protein sequence space? We present the CAMPS database (Computational Analysis of the Membrane Protein Space) containing almost 45,000 proteins with three or more predicted transmembrane helices (TMH) from 120 bacterial species. This large set of membrane proteins was subjected to single-linkage clustering using only sequence alignments covering at least 40% of the TMH present in a given family. This process yielded 266 sequence clusters with at least 15 members, roughly corresponding to membrane structural folds, sufficiently structurally homogeneous in terms of the variation of TMH number between individual sequences. These clusters were further subdivided into functionally homogeneous subclusters according to the COG (Clusters of Orthologous Groups) system as well as more stringently defined families sharing at least 30% identity. The CAMPS sequence clusters are thus designed to reflect three main levels of interest for structural genomics: fold, function, and modeling distance. We present a library of Hidden Markov Models (HMM) derived from sequence alignments of TMH at these three levels of sequence similarity. Given that 24 out of 266 clusters corresponding to membrane folds already have associated known structures, we estimate that 242 additional new structures, one for each remaining cluster, would provide structural coverage at the fold level of roughly 70% of prokaryotic membrane proteins belonging to the currently most populated families.

Bacterial Proteins↗

PubMed2003

MGD: the Mouse Genome Database.

The Mouse Genome Database (MGD) (http://www.informatics.jax.org) one component of a community database resource for the laboratory mouse, a key model organism for interpreting the human genome and for understanding human biology. MGD strives to provide an extensively integrated information resource with experimental details annotated from both literature and on-line genomic data sources. MGD curates and presents the consensus representation of genotype (sequence) to phenotype information including highly detailed information about genes and gene products. Primary foci of integration are through representations of relationships between genes, sequences and phenotypes. MGD collaborates with other bioinformatics groups to curate a definitive set of information about the laboratory mouse. Recent developments include a general implementation of database structures for controlled vocabularies and the integration of a phenotype classification system.

Alleles↗

PubMed2003

Recognition of translation initiation sites of eukaryotic genes based on an EM algorithm.

With the rapid increase of DNA databases of human and other eukaryotic model organisms, a large great number of genes need to be distinguished from the DNA databases. Exact recognition of translation initiation sites (TISs) of eukaryotic genes is very important to understand the translation initiation process, predict the detailed structure of eukaryotic genes, and annotate uncharacterized sequences. The problem has not been solved satisfactorily, especially for recognizing TISs of the eukaryotic genes with shorter first exons. It is an important task for extracting new features and finding new powerful algorithms for recognizing TISs of eukaryotic genes. In this paper, the important characteristics of shorter flanking fragments around TISs are extracted and an expectation-maximization (EM) algorithm based on incomplete data is used to recognize TISs of eukaryotic genes. The accuracy is up to 87.8% over a six-fold cross-validation test. The result shows that the identification variables are effectively extracted and the EM algorithm is a powerful tool to predict the TISs of eukaryotic genes. The algorithm also can be applied to other classification or clustering tasks in bioinformatics.

Algorithms↗

PubMed2006

PUMA2--grid-based high-throughput analysis of genomes and metabolic pathways.

The PUMA2 system (available at http://compbio.mcs.anl.gov/puma2) is an interactive, integrated bioinformatics environment for high-throughput genetic sequence analysis and metabolic reconstructions from sequence data. PUMA2 provides a framework for comparative and evolutionary analysis of genomic data and metabolic networks in the context of taxonomic and phenotypic information. Grid infrastructure is used to perform computationally intensive tasks. PUMA2 currently contains precomputed analysis of 213 prokaryotic, 22 eukaryotic, 650 mitochondrial and 1493 viral genomes and automated metabolic reconstructions for >200 organisms. Genomic data is annotated with information integrated from >20 sequence, structural and metabolic databases and ontologies. PUMA2 supports both automated and interactive expert-driven annotation of genomes, using a variety of publicly available bioinformatics tools. It also contains a suite of unique PUMA2 tools for automated assignment of gene function, evolutionary analysis of protein families and comparative analysis of metabolic pathways. PUMA2 allows users to submit batch sequence data for automated functional analysis and construction of metabolic models. The results of these analyses are made available to the users in the PUMA2 environment for further interactive sequence analysis and annotation.

Computational Biology↗

PubMed2001

Functional and structural genomics using PEDANT.

MOTIVATION: Enormous demand for fast and accurate analysis of biological sequences is fuelled by the pace of genome analysis efforts. There is also an acute need in reliable up-to-date genomic databases integrating both functional and structural information. Here we describe the current status of the PEDANT software system for high-throughput analysis of large biological sequence sets and the genome analysis server associated with it. RESULTS: The principal features of PEDANT are: (i) completely automatic processing of data using a wide range of bioinformatics methods, (ii) manual refinement of annotation, (iii) automatic and manual assignment of gene products to a number of functional and structural categories, (iv) extensive hyperlinked protein reports, and (v) advanced DNA and protein viewers. The system is easily extensible and allows to include custom methods, databases, and categories with minimal or no programming effort. PEDANT is actively used as a collaborative environment to support several on-going genome sequencing projects. The main purpose of the PEDANT genome database is to quickly disseminate well-organized information on completely sequenced and unfinished genomes. It currently includes 80 genomic sequences and in many cases serves as the only source of exhaustive information on a given genome. The database also acts as a vehicle for a number of research projects in bioinformatics. Using SQL queries, it is possible to correlate a large variety of pre-computed properties of gene products encoded in complete genomes with each other and compare them with data sets of special scientific interest. In particular, the availability of structural predictions for over 300 000 genomic proteins makes PEDANT the most extensive structural genomics resource available on the web.

Arabidopsis↗

PubMed2026

ProteoParc: A Reference Protein Database Builder for Ancient and Nonmodel Organisms.

Over the past few years, the increasing interest in analyzing the proteome of extinct and nonmodel organisms has generated a new field of research expanding the scope of proteomics. The lack of curated databases and/or molecular data from these organisms forces researchers to manually search in different public repositories for related protein sequences, either for MS/MS peptide identification or ZooMS marker annotation. This can lead to format incongruences and hinder reproducibility between studies. To address this issue, we introduce ProteoParc, a user-friendly software that builds reference databases by systematically downloading and processing protein sequences from the most widely used public repositories. The pipeline's output is a nonredundant protein database, formatted in a way to be interpreted by typical peptide identification software. Moreover, the user can adjust the database dimension and composition by applying different criteria to include only a certain number of genes or species. Thus, ProteoParc is an easy and fast, custom-made bioinformatic tool useful for future paleoproteomics analysis in ancient samples related to understudied organisms.

Databases, Protein↗

PubMed2003

Bioinformatics goes back to the future.

The need to turn raw data into knowledge has led the bioinformatics field to focus increasingly on the manipulation of information. By drawing parallels with both cryptography and artificial intelligence, we can develop an understanding of the changes that are occurring in bioinformatics, and how these changes are likely to influence the bioinformatics job market.

Artificial Intelligence↗

PubMed2002

The NCTU BioInfo Archive of biological data sets for bioinformatics research and experimentation.

UNLABELLED: Most of the current bioinformatics literature lacks an explicit and clear description of the data used in experiments when introducing or evaluating computational tools. Without the exact data set that was fed into computational tools in experiments, any mistaken preparation of the data for later experiments may lead to discrepancy in conclusion. The NCTU BioInfo Archive is a new web-based bioinformatic data archive. It serves as a test bed for evaluating computational tools, as a bridge to link other research communities with bioinformatics, and also as an environment full of motivations and possibilities to encourage more exploratory research in bioinformatics. AVAILABILITY: http://bioinfo.cis.nctu.edu.tw

Computational Biology↗

PubMed2006

BBP: Brucella genome annotation with literature mining and curation.

BACKGROUND: Brucella species are Gram-negative, facultative intracellular bacteria that cause brucellosis in humans and animals. Sequences of four Brucella genomes have been published, and various Brucella gene and genome data and analysis resources exist. A web gateway to integrate these resources will greatly facilitate Brucella research. Brucella genome data in current databases is largely derived from computational analysis without experimental validation typically found in peer-reviewed publications. It is partially due to the lack of a literature mining and curation system able to efficiently incorporate the large amount of literature data into genome annotation. It is further hypothesized that literature-based Brucella gene annotation would increase understanding of complicated Brucella pathogenesis mechanisms. RESULTS: The Brucella Bioinformatics Portal (BBP) is developed to integrate existing Brucella genome data and analysis tools with literature mining and curation. The BBP InterBru database and Brucella Genome Browser allow users to search and analyze genes of 4 currently available Brucella genomes and link to more than 20 existing databases and analysis programs. Brucella literature publications in PubMed are extracted and can be searched by a TextPresso-powered natural language processing method, a MeSH browser, a keywords search, and an automatic literature update service. To efficiently annotate Brucella genes using the large amount of literature publications, a literature mining and curation system coined Limix is developed to integrate computational literature mining methods with a PubSearch-powered manual curation and management system. The Limix system is used to quickly find and confirm 107 Brucella gene mutations including 75 genes shown to be essential for Brucella virulence. The 75 genes are further clustered using COG. In addition, 62 Brucella genetic interactions are extracted from literature publications. These results make possible more comprehensive investigation of Brucella pathogenesis. Other BBP features include publication email alert service, Brucella researchers' contact database, and discussion forum. CONCLUSION: BBP is a gateway for Brucella researchers to search, analyze, and curate Brucella genome data originated from public databases and literature. Brucella gene mutations and genetic interactions are annotated using Limix leading to better understanding of Brucella pathogenesis.

Algorithms↗