Academic literature on the topic 'Microbial genomes Bioinformatics. Database management'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Microbial genomes Bioinformatics. Database management.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Microbial genomes Bioinformatics. Database management"
1
Behl, Tapan, Ishnoor Kaur, Aayush Sehgal, Sukhbir Singh, Saurabh Bhatia, Ahmed Al-Harrasi, Gokhan Zengin, et al. "Bioinformatics Accelerates the Major Tetrad: A Real Boost for the Pharmaceutical Industry." International Journal of Molecular Sciences 22, no. 12 (June 8, 2021): 6184. http://dx.doi.org/10.3390/ijms22126184.
Full textAbstract:
With advanced technology and its development, bioinformatics is one of the avant-garde fields that has managed to make amazing progress in the pharmaceutical–medical field by modeling the infrastructural dimensions of healthcare and integrating computing tools in drug innovation, facilitating prevention, detection/more accurate diagnosis, and treatment of disorders, while saving time and money. By association, bioinformatics and pharmacovigilance promoted both sample analyzes and interpretation of drug side effects, also focusing on drug discovery and development (DDD), in which systems biology, a personalized approach, and drug repositioning were considered together with translational medicine. The role of bioinformatics has been highlighted in DDD, proteomics, genetics, modeling, miRNA discovery and assessment, and clinical genome sequencing. The authors have collated significant data from the most known online databases and publishers, also narrowing the diversified applications, in order to target four major areas (tetrad): DDD, anti-microbial research, genomic sequencing, and miRNA research and its significance in the management of current pandemic context. Our analysis aims to provide optimal data in the field by stratification of the information related to the published data in key sectors and to capture the attention of researchers interested in bioinformatics, a field that has succeeded in advancing the healthcare paradigm by introducing developing techniques and multiple database platforms, addressed in the manuscript.
2
Biaudet, Véronique, Franck Samson, and Philippe Bessières. "Micado—a network-oriented database for microbial genomes." Bioinformatics 13, no. 4 (1997): 431–38. http://dx.doi.org/10.1093/bioinformatics/13.4.431.
Full text
3
de la Cuesta-Zuluaga, Jacobo, Ruth E. Ley, and Nicholas D. Youngblut. "Struo: a pipeline for building custom databases for common metagenome profilers." Bioinformatics 36, no. 7 (November 28, 2019): 2314–15. http://dx.doi.org/10.1093/bioinformatics/btz899.
Full textAbstract:
Abstract Summary Taxonomic and functional information from microbial communities can be efficiently obtained by metagenome profiling, which requires databases of genes and genomes to which sequence reads are mapped. However, the databases that accompany metagenome profilers are not updated at a pace that matches the increase in available microbial genomes, and unifying database content across metagenome profiling tools can be cumbersome. To address this, we developed Struo, a modular pipeline that automatizes the acquisition of genomes from public repositories and the construction of custom databases for multiple metagenome profilers. The use of custom databases that broadly represent the known microbial diversity by incorporating novel genomes results in a substantial increase in mappability of reads in synthetic and real metagenome datasets. Availability and implementation Source code available for download at https://github.com/leylabmpi/Struo. Custom genome taxonomy database databases available at http://ftp.tue.mpg.de/ebio/projects/struo/. Supplementary information Supplementary data are available at Bioinformatics online.
4
Richter, Michael, Ramon Rosselló-Móra, Frank Oliver Glöckner, and Jörg Peplies. "JSpeciesWS: a web server for prokaryotic species circumscription based on pairwise genome comparison." Bioinformatics 32, no. 6 (November 16, 2015): 929–31. http://dx.doi.org/10.1093/bioinformatics/btv681.
Full textAbstract:
Abstract Summary: JSpecies Web Server (JSpeciesWS) is a user-friendly online service for in silico calculating the extent of identity between two genomes, a parameter routinely used in the process of polyphasic microbial species circumscription. The service measures the average nucleotide identity (ANI) based on BLAST+ (ANIb) and MUMmer (ANIm), as well as correlation indexes of tetra-nucleotide signatures (Tetra). In addition, it provides a Tetra Correlation Search function, which allows to rapidly compare selected genomes against a continuously updated reference database with currently about 32 000 published whole and draft genome sequences. For comparison, own genomes can be uploaded and references can be selected from the JSpeciesWS reference database. The service indicates whether two genomes share genomic identities above or below the species embracing thresholds, and serves as a fast way to allocate unknown genomes in the frame of the hitherto sequenced species. Availability and implementation: JSpeciesWS is available at http://jspecies.ribohost.com/jspeciesws. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: mrichter@ribocon.com
5
Neely, Christopher J., Elaina D. Graham, and Benjamin J. Tully. "MetaSanity: an integrated microbial genome evaluation and annotation pipeline." Bioinformatics 36, no. 15 (May 19, 2020): 4341–44. http://dx.doi.org/10.1093/bioinformatics/btaa512.
Full textAbstract:
Abstract Summary As the importance of microbiome research continues to become more prevalent and essential to understanding a wide variety of ecosystems (e.g. marine, built, host associated, etc.), there is a need for researchers to be able to perform highly reproducible and quality analysis of microbial genomes. MetaSanity incorporates analyses from 11 existing and widely used genome evaluation and annotation suites into a single, distributable workflow, thereby decreasing the workload of microbiologists by allowing for a flexible, expansive data analysis pipeline. MetaSanity has been designed to provide separate, reproducible workflows that (i) can determine the overall quality of a microbial genome, while providing a putative phylogenetic assignment, and (ii) can assign structural and functional gene annotations with varying degrees of specificity to suit the needs of the researcher. The software suite combines the results from several tools to provide broad insights into overall metabolic function. Importantly, this software provides built-in optimization for ‘big data’ analysis by storing all relevant outputs in an SQL database, allowing users to query all the results for the elements that will most impact their research. Availability and implementation MetaSanity is provided under the GNU General Public License v.3.0 and is available for download at https://github.com/cjneely10/MetaSanity. This application is distributed as a Docker image. MetaSanity is implemented in Python3/Cython and C++. Instructions for its installation and use are available within the GitHub wiki page at https://github.com/cjneely10/MetaSanity/wiki, and additional instructions are available at https://cjneely10.github.io/year-archive/. MetaSanity is optimized for users with limited programing experience. Supplementary information Supplementary data are available at Bioinformatics online.
6
Médigue, Claudine, Alexandra Calteau, Stéphane Cruveiller, Mathieu Gachet, Guillaume Gautreau, Adrien Josso, Aurélie Lajus, et al. "MicroScope—an integrated resource for community expertise of gene functions and comparative analysis of microbial genomic and metabolic data." Briefings in Bioinformatics 20, no. 4 (September 12, 2017): 1071–84. http://dx.doi.org/10.1093/bib/bbx113.
Full textAbstract:
Abstract The overwhelming list of new bacterial genomes becoming available on a daily basis makes accurate genome annotation an essential step that ultimately determines the relevance of thousands of genomes stored in public databanks. The MicroScope platform (http://www.genoscope.cns.fr/agc/microscope) is an integrative resource that supports systematic and efficient revision of microbial genome annotation, data management and comparative analysis. Starting from the results of our syntactic, functional and relational annotation pipelines, MicroScope provides an integrated environment for the expert annotation and comparative analysis of prokaryotic genomes. It combines tools and graphical interfaces to analyze genomes and to perform the manual curation of gene function in a comparative genomics and metabolic context. In this article, we describe the free-of-charge MicroScope services for the annotation and analysis of microbial (meta)genomes, transcriptomic and re-sequencing data. Then, the functionalities of the platform are presented in a way providing practical guidance and help to the nonspecialists in bioinformatics. Newly integrated analysis tools (i.e. prediction of virulence and resistance genes in bacterial genomes) and original method recently developed (the pan-genome graph representation) are also described. Integrated environments such as MicroScope clearly contribute, through the user community, to help maintaining accurate resources.
7
Quatrini, Raquel, Verónica Martínez, Hector Osorio, Felipe A. Veloso, Inti Pedroso, Jorge H. Valdés, Eugenia Jedlicki, and David S. Holmes. "Iron Homeostasis Strategies in Acidophilic Iron Oxidizers: Comparative Genomic Analyses." Advanced Materials Research 20-21 (July 2007): 531–34. http://dx.doi.org/10.4028/www.scientific.net/amr.20-21.531.
Full textAbstract:
An understanding of the physiology and metabolic complexity of microbial consortia involved in metal solubilization is a prerequisite for the rational improvement of bioleaching technologies. Among the most challenging aspects that remain to be addressed is how aerobic acidophiles, especially Fe(II)-oxidizers, contend with the paradoxical hazards of iron overload and iron deficiency, each with deleterious consequences for growth. Homeostatic mechanisms regulating the acquisition, utilization/oxidation, storage and intracellular mobilization of cellular iron are deemed to be critical for fitness and survival of bioleaching microbes. In an attempt to contribute to the comprehensive understanding of the biology and ecology of the microbial communities in bioleaching econiches, we have used comparative genomics and other bioinformatic tools to reconstruct the iron management strategies in newly sequenced acidithiobacilli and other biomining genomes available in public databases. Species-specific genes have been identified with distinctive functional roles in iron management as well as genes shared by several species in biomining consortia. Their analysis contributes to our understanding of the general survival strategies in acidic and iron loaded environments and suggests functions for genes with currently unknown functions that might reveal novel aspects of iron response in acidophiles. Comprehensive examination of the occurrence and conservation of regulatory functions and regulatory sites also allowed the prediction of the metal regulatory networks for these biomining microbes.
8
Doster, Enrique, Steven M. Lakin, Christopher J. Dean, Cory Wolfe, Jared G. Young, Christina Boucher, Keith E. Belk, Noelle R. Noyes, and Paul S. Morley. "MEGARes 2.0: a database for classification of antimicrobial drug, biocide and metal resistance determinants in metagenomic sequence data." Nucleic Acids Research 48, no. D1 (November 13, 2019): D561—D569. http://dx.doi.org/10.1093/nar/gkz1010.
Full textAbstract:
Abstract Antimicrobial resistance (AMR) is a threat to global public health and the identification of genetic determinants of AMR is a critical component to epidemiological investigations. High-throughput sequencing (HTS) provides opportunities for investigation of AMR across all microbial genomes in a sample (i.e. the metagenome). Previously, we presented MEGARes, a hand-curated AMR database and annotation structure developed to facilitate the analysis of AMR within metagenomic samples (i.e. the resistome). Along with MEGARes, we released AmrPlusPlus, a bioinformatics pipeline that interfaces with MEGARes to identify and quantify AMR gene accessions contained within a metagenomic sequence dataset. Here, we present MEGARes 2.0 (https://megares.meglab.org), which incorporates previously published resistance sequences for antimicrobial drugs, while also expanding to include published sequences for metal and biocide resistance determinants. In MEGARes 2.0, the nodes of the acyclic hierarchical ontology include four antimicrobial compound types, 57 classes, 220 mechanisms of resistance, and 1,345 gene groups that classify the 7,868 accessions. In addition, we present an updated version of AmrPlusPlus (AMR ++ version 2.0), which improves accuracy of classifications, as well as expanding scalability and usability.
9
Wickramarachchi, Anuradha, Vijini Mallawaarachchi, Vaibhav Rajan, and Yu Lin. "MetaBCC-LR: metagenomics binning by coverage and composition for long reads." Bioinformatics 36, Supplement_1 (July 1, 2020): i3—i11. http://dx.doi.org/10.1093/bioinformatics/btaa441.
Full textAbstract:
Abstract Motivation Metagenomics studies have provided key insights into the composition and structure of microbial communities found in different environments. Among the techniques used to analyse metagenomic data, binning is considered a crucial step to characterize the different species of micro-organisms present. The use of short-read data in most binning tools poses several limitations, such as insufficient species-specific signal, and the emergence of long-read sequencing technologies offers us opportunities to surmount them. However, most current metagenomic binning tools have been developed for short reads. The few tools that can process long reads either do not scale with increasing input size or require a database with reference genomes that are often unknown. In this article, we present MetaBCC-LR, a scalable reference-free binning method which clusters long reads directly based on their k-mer coverage histograms and oligonucleotide composition. Results We evaluate MetaBCC-LR on multiple simulated and real metagenomic long-read datasets with varying coverages and error rates. Our experiments demonstrate that MetaBCC-LR substantially outperforms state-of-the-art reference-free binning tools, achieving ∼13% improvement in F1-score and ∼30% improvement in ARI compared to the best previous tools. Moreover, we show that using MetaBCC-LR before long-read assembly helps to enhance the assembly quality while significantly reducing the assembly cost in terms of time and memory usage. The efficiency and accuracy of MetaBCC-LR pave the way for more effective long-read-based metagenomics analyses to support a wide range of applications. Availability and implementation The source code is freely available at: https://github.com/anuradhawick/MetaBCC-LR. Supplementary information Supplementary data are available at Bioinformatics online.
10
Wu, Meng, Qingdai Li, and Hongbing Wang. "Identification of Novel Biomarkers Associated With the Prognosis and Potential Pathogenesis of Breast Cancer via Integrated Bioinformatics Analysis." Technology in Cancer Research & Treatment 20 (January 1, 2021): 153303382199208. http://dx.doi.org/10.1177/1533033821992081.
Full textAbstract:
Background: Breast cancer is the most commonly diagnosed malignancy and a major cause of cancer-related deaths in women globally. Identification of novel prognostic and pathogenesis biomarkers play a pivotal role in the management of the disease. Methods: Three data sets from the GEO database were used to identify differentially expressed genes (DEGs) in breast cancer. Gene Ontology (GO) enrichment and Kyoto Encyclopaedia of Genes and Genomes pathway analyses were performed to elucidate the functional roles of the DEGs. Besides, we investigated the translational and protein expression levels and survival data of the DEGs in patients with breast cancer from the Gene Expression Profiling Interactive Analysis (GEPIA), Oncomine, Human Protein Atlas, and Kaplan Meier plotter tool databases. The corresponding change in the expression level of microRNAs in the DEGs was also predicted using miRWalk and TargetScan, and the expression profiles were analyzed using OncomiR. Finally, the expression of novel DEGs were validated in Chinese breast cancer tissues by RT-qPCR. Results: A total of 46 DEGs were identified, and GO analysis revealed that these genes were mainly associated with biological processes involved in fatty acid, lipid localization, and regulation of lipid metabolism. Two novel biomarkers, ADH1A and IGSF10, and 4 other genes ( APOD, KIT, RBP4, and SFRP1) that were implicated in the prognosis and pathogenesis of breast cancer, exhibited low expression levels in breast cancer tissues. Besides, 14/25 microRNAs targeting 6 genes were first predicted to be associated with breast cancer prognosis. RT-qPCR results of ADH1A and IGSF10 expression in Chinese breast cancer tissues were consistent with the database analysis and showed significant down-regulation. Conclusion: ADH1A, IGSF10, and the 14 microRNAs were found to be potential novel biomarkers for the diagnosis, treatment, and prognosis of breast cancer.
Dissertations / Theses on the topic "Microbial genomes Bioinformatics. Database management"
1
Sanchez, Rhea I. "Annotation consistency tool : the assessment of JCVI microbial genome annotations /." Online version of thesis, 2009. http://hdl.handle.net/1850/10653.
Full textBook chapters on the topic "Microbial genomes Bioinformatics. Database management"
1
Bhatt, Pankaj. "Insilico Tools to Study the Bioremediation in Microorganisms." In Handbook of Research on Microbial Tools for Environmental Waste Management, 389–95. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3540-9.ch018.
Full textAbstract:
Bioinformatics is the new area of science to study various living organisms, plants and animals. Bioremediation is the removal of toxic pollutants from the environment using microorganisms. Many of the databases are available online and can be used for the study of the microorganism genomics, transcriptomics, proteomics. This chapter mainly focuses the uses of recent databases and tools for the exploration of microorganisms.
2
Udoh, Emmanuel, and Salim Bhuiyan. "C-MICRA." In Handbook of Research on Innovations in Database Technologies and Applications, 573–80. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-60566-242-8.ch061.
Full textAbstract:
In the field of bioinformatics, small to large data sets of genes, proteins, and genomes are analyzed for biological significance. A technology that has been in the forefront of generating large amounts of gene data is the microarray or hybridization technique. It has been instrumental in the success of the human genome project and paved the way for a new era of genetic screening, testing, and diagnostics (Scheena, 2003). The microarray data set can be made of thousands of rows and columns. It often contains missing values, exhibits high-dimensional attributes, and is generally too large for manual management or examination (Tseng & Kao, 2005; Turner, Bailey, Krzanowski, & Hemingway, 2005). Database technology is necessary for the extraction, sorting, and analyzing of microarray data sets.
3
Mangaraj, B. K., and Upali Aparajita. "Cultural Dimension in the Future of Pervasive Computing." In Ubiquitous and Pervasive Computing, 974–92. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-960-1.ch060.
Full textAbstract:
Microorganisms are ubiquitous in their presence. They are present in air, soil, water, and all kinds of living creatures. Varieties of microbes have been linked to diseases of humans, animals, and plants. Advances in molecular biology, electronics, nanotechnology, computer sciences, and information technology have made it possible to hybridize these to create ubiquitous devices and biosensors that would indicate presence of microbial agents in water, foods, air, hospitals, animal farms, and other environments. Analyses of microbial genomes and phylogenies have become increasingly important in the tracking and investigation of events leading to spread of microbial diseases and biocrimes. The capability of microorganisms to communicate with similar as well as different microorganisms, the ability to react to the environmental changes, and most of all, the intelligence to manage themselves without the need for supervision during deployment and operation; makes them attractive agents for use in Biosensors. Biosensors such as genetically engineered bacteria have been proven useful. It appears possible to develop biosensors that could detect the presence of biocrime/bioterror agents in diverse environments. Ubiquitous computing technology has the potential to develop integrated small devices which could detect bioterrorism agents. Similarly, pervasive computing could be a tool to monitor the microbial pollution in water, milk, and other edible commodities. Microbial forensics has become an important field for research and development due to increased threats of biocrimes. Microbial forensics requires utilization of diverse data that are acquired through standard processes in distributed locations. Technologies for data production are evolving rapidly, especially with respect to instrumentation and techniques that produce high-resolution data about the molecular constituents of living cells (DNA, mRNA, proteins, and metabolites) that are used as microbial signatures/fingerprints. Both bioinformatics and computational biology have grown over the last 20 years, and diverse database systems and analytical tools have been developed and deployed. Some public domain resources, such as GenBank, have become very important resources of research on a global scale. Effective responses to natural, accidental, or intentional outbreaks of infectious diseases in humans, livestock, and agricultural crops, will require that the information be easily accessed in real-time or near real-time. Flexible, decentralized, modular information system architectures, able to adapt to evolving requirements and available on the Internet, are needed.