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1.
Methods Mol Biol ; 2802: 573-586, 2024.
Article in English | MEDLINE | ID: mdl-38819572

ABSTRACT

The Eukaryotic Pathogen, Vector and Host Informatics Resources ( VEuPathDB.org ) provide free online access to omic data from eukaryotic protozoan and fungal pathogens, arthropod vectors of disease, and host responses to pathogen infection. The goal of VEuPathDB is to make data easily accessible, findable, and importantly, re-usable by laboratory scientists. All integrated data and analyses follow standard workflows and methods to ensure data accuracy and enable data interoperability. Integrated data include genomes and annotation, transcriptomic (e.g., single-cell/bulk RNA-sequence and microarray data), proteomic (e.g., mass spectrometry evidence and quantitative data), isolate sequencing data used for variant calling and copy number variation determination, epigenomics, whole-genome phenotyping data (e.g., CRISPR screens and large-scale imaging and subcellular localization data), etc. Standard analyses provide additional data such as InterPro domains, signal peptide and transmembrane domain predictions, and metabolic pathways. Comparative genomic analysis in VEuPathDB is facilitated by leveraging orthology to enable the transformation of results between organisms and identifying genes with specific phyletic patterns. In addition, synteny between genomes is facilitated by shading orthologs across species and strains. Accessibility to and re-usability of the data is made possible through specialized searches and a graphical search strategy system that enables scientists to build in silico experiments combining results from multiple experiments with diverse data types.


Subject(s)
Computational Biology , Computational Biology/methods , Genomics/methods , Proteomics/methods , Software , Animals , Databases, Genetic , Humans , Host-Pathogen Interactions/genetics , Internet
2.
bioRxiv ; 2024 May 15.
Article in English | MEDLINE | ID: mdl-38766159

ABSTRACT

Brain arteriovenous malformations (bAVMs) are direct connections between arteries and veins that remodel into a complex nidus susceptible to rupture and hemorrhage. Most sporadic bAVMs feature somatic activating mutations within KRAS, and endothelial-specific expression of the constitutively active variant KRASG12D models sporadic bAVM in mice. By leveraging 3D-based micro-CT imaging, we demonstrate that KRASG12D-driven bAVMs arise in stereotypical anatomical locations within the murine brain, which coincide with high endogenous Kras expression. We extend these analyses to show that a distinct variant, KRASG12C, also generates bAVMs in predictable locations. Analysis of 15,000 human patients revealed that, similar to murine models, bAVMs preferentially occur in distinct regions of the adult brain. Furthermore, bAVM location correlates with hemorrhagic frequency. Quantification of 3D imaging revealed that G12D and G12C alter vessel density, tortuosity, and diameter within the mouse brain. Notably, aged G12D mice feature increased lethality, as well as impaired cognition and motor function. Critically, we show that pharmacological blockade of the downstream kinase, MEK, after lesion formation ameliorates KRASG12D-driven changes in the murine cerebrovasculature and may also impede bAVM progression in human pediatric patients. Collectively, these data show that distinct KRAS variants drive bAVMs in similar patterns and suggest MEK inhibition represents a non-surgical alternative therapy for sporadic bAVM.

3.
Genetics ; 227(1)2024 05 07.
Article in English | MEDLINE | ID: mdl-38529759

ABSTRACT

FungiDB (https://fungidb.org) serves as a valuable online resource that seamlessly integrates genomic and related large-scale data for a wide range of fungal and oomycete species. As an integral part of the VEuPathDB Bioinformatics Resource Center (https://veupathdb.org), FungiDB continually integrates both published and unpublished data addressing various aspects of fungal biology. Established in early 2011, the database has evolved to support 674 datasets. The datasets include over 300 genomes spanning various taxa (e.g. Ascomycota, Basidiomycota, Blastocladiomycota, Chytridiomycota, Mucoromycota, as well as Albuginales, Peronosporales, Pythiales, and Saprolegniales). In addition to genomic assemblies and annotation, over 300 extra datasets encompassing diverse information, such as expression and variation data, are also available. The resource also provides an intuitive web-based interface, facilitating comprehensive approaches to data mining and visualization. Users can test their hypotheses and navigate through omics-scale datasets using a built-in search strategy system. Moreover, FungiDB offers capabilities for private data analysis via the integrated VEuPathDB Galaxy platform. FungiDB also permits genome improvements by capturing expert knowledge through the User Comments system and the Apollo genome annotation editor for structural and functional gene curation. FungiDB facilitates data exploration and analysis and contributes to advancing research efforts by capturing expert knowledge for fungal and oomycete species.


Subject(s)
Computational Biology , Databases, Genetic , Fungi , Internet , Oomycetes , Oomycetes/genetics , Fungi/genetics , Computational Biology/methods , Genome, Fungal , Genomics/methods , Software
4.
bioRxiv ; 2024 Jan 18.
Article in English | MEDLINE | ID: mdl-38293033

ABSTRACT

Babesiosis, caused by protozoan parasites of the genus Babesia , is an emerging tick-borne disease of significance for both human and animal health. Babesia parasites infect erythrocytes of vertebrate hosts where they develop and multiply rapidly to cause the pathological symptoms associated with the disease. The identification of various Babesia species underscores the ongoing risk of new zoonotic pathogens capable of infecting humans, a concern amplified by anthropogenic activities and environmental shifts impacting the distribution and transmission dynamics of parasites, their vectors, and reservoir hosts. One such species, Babesia MO1, previously implicated in severe cases of human babesiosis in the midwestern United States, was initially considered closely related to B. divergens , the predominant agent of human babesiosis in Europe. Yet, uncertainties persist regarding whether these pathogens represent distinct variants of the same species or are entirely separate species. We show that although both B. MO1 and B. divergens share similar genome sizes, comprising three nuclear chromosomes, one linear mitochondrial chromosome, and one circular apicoplast chromosome, major differences exist in terms of genomic sequence divergence, gene functions, transcription profiles, replication rates and susceptibility to antiparasitic drugs. Furthermore, both pathogens have evolved distinct classes of multigene families, crucial for their pathogenicity and adaptation to specific mammalian hosts. Leveraging genomic information for B. MO1, B. divergens , and other members of the Babesiidae family within Apicomplexa provides valuable insights into the evolution, diversity, and virulence of these parasites. This knowledge serves as a critical tool in preemptively addressing the emergence and rapid transmission of more virulent strains.

5.
Nucleic Acids Res ; 52(D1): D808-D816, 2024 Jan 05.
Article in English | MEDLINE | ID: mdl-37953350

ABSTRACT

The Eukaryotic Pathogen, Vector and Host Informatics Resource (VEuPathDB, https://veupathdb.org) is a Bioinformatics Resource Center funded by the National Institutes of Health with additional funding from the Wellcome Trust. VEuPathDB supports >600 organisms that comprise invertebrate vectors, eukaryotic pathogens (protists and fungi) and relevant free-living or non-pathogenic species or hosts. Since 2004, VEuPathDB has analyzed omics data from the public domain using contemporary bioinformatic workflows, including orthology predictions via OrthoMCL, and integrated the analysis results with analysis tools, visualizations, and advanced search capabilities. The unique data mining platform coupled with >3000 pre-analyzed data sets facilitates the exploration of pertinent omics data in support of hypothesis driven research. Comparisons are easily made across data sets, data types and organisms. A Galaxy workspace offers the opportunity for the analysis of private large-scale datasets and for porting to VEuPathDB for comparisons with integrated data. The MapVEu tool provides a platform for exploration of spatially resolved data such as vector surveillance and insecticide resistance monitoring. To address the growing body of omics data and advances in laboratory techniques, VEuPathDB has added several new data types, searches and features, improved the Galaxy workspace environment, redesigned the MapVEu interface and updated the infrastructure to accommodate these changes.


Subject(s)
Computational Biology , Eukaryota , Animals , Computational Biology/methods , Invertebrates , Databases, Factual
6.
Nat Microbiol ; 8(5): 845-859, 2023 05.
Article in English | MEDLINE | ID: mdl-37055610

ABSTRACT

Babesiosis is a malaria-like disease in humans and animals that is caused by Babesia species, which are tick-transmitted apicomplexan pathogens. Babesia duncani causes severe to lethal infection in humans, but despite the risk that this parasite poses as an emerging pathogen, little is known about its biology, metabolic requirements or pathogenesis. Unlike other apicomplexan parasites that infect red blood cells, B. duncani can be continuously cultured in vitro in human erythrocytes and can infect mice resulting in fulminant babesiosis and death. We report comprehensive, detailed molecular, genomic, transcriptomic and epigenetic analyses to gain insights into the biology of B. duncani. We completed the assembly, 3D structure and annotation of its nuclear genome, and analysed its transcriptomic and epigenetics profiles during its asexual life cycle stages in human erythrocytes. We used RNA-seq data to produce an atlas of parasite metabolism during its intraerythrocytic life cycle. Characterization of the B. duncani genome, epigenome and transcriptome identified classes of candidate virulence factors, antigens for diagnosis of active infection and several attractive drug targets. Furthermore, metabolic reconstitutions from genome annotation and in vitro efficacy studies identified antifolates, pyrimethamine and WR-99210 as potent inhibitors of B. duncani to establish a pipeline of small molecules that could be developed as effective therapies for the treatment of human babesiosis.


Subject(s)
Babesia , Babesiosis , Ticks , Animals , Humans , Mice , Babesia/genetics , Babesiosis/drug therapy , Multiomics , Erythrocytes/parasitology
7.
PLoS Negl Trop Dis ; 17(1): e0011058, 2023 01.
Article in English | MEDLINE | ID: mdl-36656904

ABSTRACT

Parasitic diseases caused by kinetoplastid parasites are a burden to public health throughout tropical and subtropical regions of the world. TriTrypDB (https://tritrypdb.org) is a free online resource for data mining of genomic and functional data from these kinetoplastid parasites and is part of the VEuPathDB Bioinformatics Resource Center (https://veupathdb.org). As of release 59, TriTrypDB hosts 83 kinetoplastid genomes, nine of which, including Trypanosoma brucei brucei TREU927, Trypanosoma cruzi CL Brener and Leishmania major Friedlin, undergo manual curation by integrating information from scientific publications, high-throughput assays and user submitted comments. TriTrypDB also integrates transcriptomic, proteomic, epigenomic, population-level and isolate data, functional information from genome-wide RNAi knock-down and fluorescent tagging, and results from automated bioinformatics analysis pipelines. TriTrypDB offers a user-friendly web interface embedded with a genome browser, search strategy system and bioinformatics tools to support custom in silico experiments that leverage integrated data. A Galaxy workspace enables users to analyze their private data (e.g., RNA-sequencing, variant calling, etc.) and explore their results privately in the context of publicly available information in the database. The recent addition of an annotation platform based on Apollo enables users to provide both functional and structural changes that will appear as 'community annotations' immediately and, pending curatorial review, will be integrated into the official genome annotation.


Subject(s)
Kinetoplastida , Software , User-Computer Interface , Proteomics , Genomics/methods , Computational Biology/methods , Databases, Genetic , Internet
8.
Curr Opin Insect Sci ; 50: 100860, 2022 04.
Article in English | MEDLINE | ID: mdl-34864248

ABSTRACT

VectorBase (VectorBase.org) is part of the VEuPathDB Bioinformatics Resource Center, providing free online access to multi-omics and population biology data, focusing on arthropod vectors and invertebrates of importance to human health. VectorBase includes genomics and functional genomics data from bed bugs, biting midges, body lice, kissing bugs, mites, mosquitoes, sand flies, ticks, tsetse flies, stable flies, house flies, fruit flies, and a snail intermediate host. Tools include the Search Strategy system and MapVEu, enabling users to interrogate and visualize diverse 'omics and population-level data using a graphical interface (no programming experience required). Users can also analyze their own private data, such as transcriptomic sequences, exploring their results in the context of other publicly-available information in the database. Help Desk: help@vectorbase.org.


Subject(s)
Computational Biology , Culicidae , Animals , Genomics , Humans , Invertebrates/genetics , Mosquito Vectors
9.
Nucleic Acids Res ; 50(D1): D898-D911, 2022 01 07.
Article in English | MEDLINE | ID: mdl-34718728

ABSTRACT

The Eukaryotic Pathogen, Vector and Host Informatics Resource (VEuPathDB, https://veupathdb.org) represents the 2019 merger of VectorBase with the EuPathDB projects. As a Bioinformatics Resource Center funded by the National Institutes of Health, with additional support from the Welllcome Trust, VEuPathDB supports >500 organisms comprising invertebrate vectors, eukaryotic pathogens (protists and fungi) and relevant free-living or non-pathogenic species or hosts. Designed to empower researchers with access to Omics data and bioinformatic analyses, VEuPathDB projects integrate >1700 pre-analysed datasets (and associated metadata) with advanced search capabilities, visualizations, and analysis tools in a graphic interface. Diverse data types are analysed with standardized workflows including an in-house OrthoMCL algorithm for predicting orthology. Comparisons are easily made across datasets, data types and organisms in this unique data mining platform. A new site-wide search facilitates access for both experienced and novice users. Upgraded infrastructure and workflows support numerous updates to the web interface, tools, searches and strategies, and Galaxy workspace where users can privately analyse their own data. Forthcoming upgrades include cloud-ready application architecture, expanded support for the Galaxy workspace, tools for interrogating host-pathogen interactions, and improved interactions with affiliated databases (ClinEpiDB, MicrobiomeDB) and other scientific resources, and increased interoperability with the Bacterial & Viral BRC.


Subject(s)
Databases, Factual , Disease Vectors/classification , Host-Pathogen Interactions/genetics , Phenotype , User-Computer Interface , Animals , Apicomplexa/classification , Apicomplexa/genetics , Apicomplexa/pathogenicity , Bacteria/classification , Bacteria/genetics , Bacteria/pathogenicity , Communicable Diseases/microbiology , Communicable Diseases/parasitology , Communicable Diseases/pathology , Communicable Diseases/transmission , Computational Biology/methods , Data Mining/methods , Diplomonadida/classification , Diplomonadida/genetics , Diplomonadida/pathogenicity , Fungi/classification , Fungi/genetics , Fungi/pathogenicity , Humans , Insecta/classification , Insecta/genetics , Insecta/pathogenicity , Internet , Nematoda/classification , Nematoda/genetics , Nematoda/pathogenicity , Phylogeny , Virulence , Workflow
10.
Methods Mol Biol ; 2071: 27-47, 2020.
Article in English | MEDLINE | ID: mdl-31758445

ABSTRACT

ToxoDB is a free online resource that provides access to genomic and functional genomic data. All data is made available through an intuitive queryable interface that enables scientists to build in silico experiments and develop testable hypothesis. The resource contains 32 fully sequenced and annotated genomes, with genomic sequence from multiple strains available for variant detection and copy number variation analysis. In addition to genomic sequence data, ToxoDB contains numerous functional genomic datasets including microarray, RNAseq, proteomics, ChIP-seq, and phenotypic data. In addition, results from a number of whole-genome analyses are incorporated including mapping to orthology clusters which allows users to leverage phylogenetic relationships in their analyses. Integration of primary data is made possible through a private galaxy interface and custom export tools that allow users to interrogate their own results in the context of all other data in the database.


Subject(s)
Computational Biology/methods , Genomics/methods , Toxoplasma/genetics , Toxoplasma/metabolism , Chromatin Immunoprecipitation Sequencing , Genome-Wide Association Study , Proteomics/methods
12.
Gates Open Res ; 3: 1661, 2019.
Article in English | MEDLINE | ID: mdl-32047873

ABSTRACT

The concept of open data has been gaining traction as a mechanism to increase data use, ensure that data are preserved over time, and accelerate discovery. While epidemiology data sets are increasingly deposited in databases and repositories, barriers to access still remain. ClinEpiDB was constructed as an open-access online resource for clinical and epidemiologic studies by leveraging the extensive web toolkit and infrastructure of the Eukaryotic Pathogen Database Resources (EuPathDB; a collection of databases covering 170+ eukaryotic pathogens, relevant related species, and select hosts) combined with a unified semantic web framework. Here we present an intuitive point-and-click website that allows users to visualize and subset data directly in the ClinEpiDB browser and immediately explore potential associations. Supporting study documentation aids contextualization, and data can be downloaded for advanced analyses. By facilitating access and interrogation of high-quality, large-scale data sets, ClinEpiDB aims to spur collaboration and discovery that improves global health.

13.
J Fungi (Basel) ; 4(1)2018 Mar 20.
Article in English | MEDLINE | ID: mdl-30152809

ABSTRACT

FungiDB (fungidb.org) is a free online resource for data mining and functional genomics analysis for fungal and oomycete species. FungiDB is part of the Eukaryotic Pathogen Genomics Database Resource (EuPathDB, eupathdb.org) platform that integrates genomic, transcriptomic, proteomic, and phenotypic datasets, and other types of data for pathogenic and nonpathogenic, free-living and parasitic organisms. FungiDB is one of the largest EuPathDB databases containing nearly 100 genomes obtained from GenBank, Aspergillus Genome Database (AspGD), The Broad Institute, Joint Genome Institute (JGI), Ensembl, and other sources. FungiDB offers a user-friendly web interface with embedded bioinformatics tools that support custom in silico experiments that leverage FungiDB-integrated data. In addition, a Galaxy-based workspace enables users to generate custom pipelines for large-scale data analysis (e.g., RNA-Seq, variant calling, etc.). This review provides an introduction to the FungiDB resources and focuses on available features, tools, and queries and how they can be used to mine data across a diverse range of integrated FungiDB datasets and records.

14.
Methods Mol Biol ; 1757: 69-113, 2018.
Article in English | MEDLINE | ID: mdl-29761457

ABSTRACT

Fighting infections and developing novel drugs and vaccines requires advanced knowledge of pathogen's biology. Readily accessible genomic, functional genomic, and population data aids biological and translational discovery. The Eukaryotic Pathogen Database Resources ( http://eupathdb.org ) are data mining resources that support hypothesis driven research by facilitating the discovery of meaningful biological relationships from large volumes of data. The resource encompasses 13 sites that support over 170 species including pathogenic protists, oomycetes, and fungi as well as evolutionarily related nonpathogenic species. EuPathDB integrates preanalyzed data with advanced search capabilities, data visualization, analysis tools and a comprehensive record system in a graphical interface that does not require prior computational skills. This chapter describes guiding concepts common across EuPathDB sites and illustrates the powerful data mining capabilities of some of the available tools and features.


Subject(s)
Databases, Genetic , Genomics , Parasites/genetics , Animals , Computational Biology/methods , Data Mining , Eukaryotic Cells , Genome, Protozoan , Genomics/methods , Metabolic Networks and Pathways , Parasites/metabolism , Proteomics/methods , Software , Transcriptome , User-Computer Interface , Web Browser
15.
Fungal Genet Biol ; 115: 90-93, 2018 06.
Article in English | MEDLINE | ID: mdl-29355605

ABSTRACT

There is no comprehensive storage for generated mutants of Fusarium graminearum or data associated with these mutants. Instead, researchers relied on several independent and non-integrated databases. FgMutantDb was designed as a simple spreadsheet that is accessible globally on the web that will function as a centralized source of information on F. graminearum mutants. FgMutantDb aids in the maintenance and sharing of mutants within a research community. It will serve also as a platform for disseminating prepublication results as well as negative results that often go unreported. Additionally, the highly curated information on mutants in FgMutantDb will be shared with other databases (FungiDB, Ensembl, PhytoPath, and PHI-base) through updating reports. Here we describe the creation and potential usefulness of FgMutantDb to the F. graminearum research community, and provide a tutorial on its use. This type of database could be easily emulated for other fungal species.


Subject(s)
Databases, Genetic , Fusarium/genetics , Genome, Fungal/genetics , Internet , Mutation , Plant Diseases/genetics , Plant Diseases/microbiology
16.
Nucleic Acids Res ; 45(D1): D581-D591, 2017 01 04.
Article in English | MEDLINE | ID: mdl-27903906

ABSTRACT

The Eukaryotic Pathogen Genomics Database Resource (EuPathDB, http://eupathdb.org) is a collection of databases covering 170+ eukaryotic pathogens (protists & fungi), along with relevant free-living and non-pathogenic species, and select pathogen hosts. To facilitate the discovery of meaningful biological relationships, the databases couple preconfigured searches with visualization and analysis tools for comprehensive data mining via intuitive graphical interfaces and APIs. All data are analyzed with the same workflows, including creation of gene orthology profiles, so data are easily compared across data sets, data types and organisms. EuPathDB is updated with numerous new analysis tools, features, data sets and data types. New tools include GO, metabolic pathway and word enrichment analyses plus an online workspace for analysis of personal, non-public, large-scale data. Expanded data content is mostly genomic and functional genomic data while new data types include protein microarray, metabolic pathways, compounds, quantitative proteomics, copy number variation, and polysomal transcriptomics. New features include consistent categorization of searches, data sets and genome browser tracks; redesigned gene pages; effective integration of alternative transcripts; and a EuPathDB Galaxy instance for private analyses of a user's data. Forthcoming upgrades include user workspaces for private integration of data with existing EuPathDB data and improved integration and presentation of host-pathogen interactions.


Subject(s)
Databases, Genetic , Eukaryota , Genomics/methods , Host-Pathogen Interactions/genetics , Metagenome , Metagenomics/methods , Software , Computational Biology/methods , DNA Copy Number Variations , Gene Expression Profiling , Proteomics , Web Browser
17.
Am J Trop Med Hyg ; 93(3 Suppl): 87-98, 2015 Sep.
Article in English | MEDLINE | ID: mdl-26259940

ABSTRACT

The study of the three protagonists in malaria-the Plasmodium parasite, the Anopheles mosquito, and the human host-is key to developing methods to control and eventually eliminate the disease. Genomic technologies, including the recent development of next-generation sequencing, enable interrogation of this triangle to an unprecedented level of scrutiny, and promise exciting progress toward real-time epidemiology studies and the study of evolutionary adaptation. We discuss the use of genomics by the International Centers of Excellence for Malaria Research, a network of field sites and laboratories in malaria-endemic countries that undertake cutting-edge research, training, and technology transfer in malarious countries of the world.


Subject(s)
Anopheles/genetics , Genetics, Population , Malaria/genetics , Plasmodium/genetics , Animals , Genetic Markers/genetics , Genetics, Population/methods , Genome-Wide Association Study , Genotyping Techniques , Humans , International Cooperation , Malaria/epidemiology , Malaria/parasitology , Malaria/prevention & control , Microsatellite Repeats/genetics , Plasmodium falciparum/genetics , Plasmodium vivax/genetics , Sequence Analysis, DNA
18.
Am J Trop Med Hyg ; 93(3 Suppl): 124-132, 2015 Sep.
Article in English | MEDLINE | ID: mdl-26259944

ABSTRACT

Data generated during the course of research activities carried out by the International Centers of Excellence for Malaria Research (ICEMR) is heterogeneous, large, and multi-scaled. The complexity of federated and global data operations and the diverse uses planned for the data pose tremendous challenges and opportunities for collaborative research. In this article, we present the foundational principles for data management across the ICEMR Program, the logistics associated with multiple aspects of the data life cycle, and describe a pilot centralized web information system created in PlasmoDB to query a subset of this data. The paradigm proposed as a solution for the data operations in the ICEMR Program is widely applicable to large, multifaceted research projects, and could be reproduced in other contexts that require sophisticated data management.


Subject(s)
Information Management/organization & administration , International Cooperation , Malaria/epidemiology , Biomedical Research/organization & administration , Cooperative Behavior , Databases, Factual , Humans , Information Management/ethics , Malaria/prevention & control , Plasmodium , Quality Control , Software
19.
Bioinformatics ; 31(9): 1496-8, 2015 May 01.
Article in English | MEDLINE | ID: mdl-25573919

ABSTRACT

MOTIVATION: RNA-Seq is a method for profiling transcription using high-throughput sequencing and is an important component of many research projects that wish to study transcript isoforms, condition specific expression and transcriptional structure. The methods, tools and technologies used to perform RNA-Seq analysis continue to change, creating a bioinformatics challenge for researchers who wish to exploit these data. Resources that bring together genomic data, analysis tools, educational material and computational infrastructure can minimize the overhead required of life science researchers. RESULTS: RNA-Rocket is a free service that provides access to RNA-Seq and ChIP-Seq analysis tools for studying infectious diseases. The site makes available thousands of pre-indexed genomes, their annotations and the ability to stream results to the bioinformatics resources VectorBase, EuPathDB and PATRIC. The site also provides a combination of experimental data and metadata, examples of pre-computed analysis, step-by-step guides and a user interface designed to enable both novice and experienced users of RNA-Seq data. AVAILABILITY AND IMPLEMENTATION: RNA-Rocket is available at rnaseq.pathogenportal.org. Source code for this project can be found at github.com/cidvbi/PathogenPortal. CONTACT: anwarren@vt.edu SUPPLEMENTARY INFORMATION: Supplementary materials are available at Bioinformatics online.


Subject(s)
Gene Expression Profiling/methods , High-Throughput Screening Assays/methods , Sequence Analysis, RNA/methods , Software , Animals , Bacteria/genetics , Disease Vectors , Genomics , Parasites/genetics
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