International Journal of Bioinformatics Research and Applications (Int J Bioinformatics Res Appl)

Publisher: Inderscience

Journal description

Bioinformatics is a new scientific discipline that combines biology, computer science, mathematics, and statistics into a broad-based field that will have profound impacts on all fields of biology. Bioinformatics is expected to substantially impact on scientific, engineering and economic development of the world. Research and development in bioinformatics and computational biology require the cooperation of specialists from the fields of biology, computer science, mathematics, statistics, physics, and such related sciences. It is the comprehensive application of mathematics (e.g., probability and graph theory), statistics, science (e.g., biochemistry), and computer science (e.g., computer algorithms and machine learning) to the understanding of living systems. Bioinformatics is fast emerging as an important discipline for academic research and industrial application. The large size of biological data sets, inherent complexity of biological problems and the ability to deal with error-prone data all result in special requirements such as large memory space and huge computation time. IJBRA addresses the most innovative developments, research issues and solutions in bioinformatics and computational biology and their applications.

Current impact factor: 0.00

Impact Factor Rankings

Additional details

5-year impact 0.00
Cited half-life 0.00
Immediacy index 0.00
Eigenfactor 0.00
Article influence 0.00
Website International Journal of Bioinformatics Research and Applications website
Other titles Bioinformatics research and applicatons, IJBRA
ISSN 1744-5485
OCLC 300961439
Material type Periodical, Internet resource
Document type Internet Resource, Journal / Magazine / Newspaper

Publisher details

Inderscience

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author cannot archive a post-print version
  • Restrictions
    • 6 months embargo
  • Conditions
    • Cannot archive until publication
    • Author's pre-print and Author's post-print on author's personal website, institutional repository or subject repository
    • Publisher copyright and source must be acknowledged
    • Must link to journal webpage and /or DOI
    • Publisher's version/PDF cannot be used, unless covered by funding agency rules
    • Authors covered by funding agency rules, may post the Publisher's Version/PDF in subject repositories after a 6 months embargo
    • Reviewed 10/02/2014
    • Author's post-print equates to Inderscience's Proof
  • Classification
    yellow

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Laptop computers have become an important and essential for students to acquire for their studies, and careers. laptop computers in the classroom can lead to positive education outcomes. This study aims to examine student’s perceptions concerning the usage of laptop and the acceptance of laptop in the AZZAYTUNA UNIVERSITY in LIBYA. Also, to investigates the level of usage on the use of Laptop computers among students, and to examines the relationship between the perceptions of students concerning the use
    No preview · Article · Aug 2016 · International Journal of Bioinformatics Research and Applications
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    ABSTRACT: Owing to their sessile nature, plants experience a variety of environmental stresses, but tolerance to these adverse conditions is a very complex phenomenon. Among all stresses, heat stress is the most important constraint that affects plant yield in rain-fed areas. To shed some light on candidate genes involved in heat stress, sequences potentially associated with heat shock resistance were retrieved and identified by in silico analysis using the public sequence database of various plants. A total of 30,000 EST sequences were mined and 24 putative ESTs associated with heat stress were picked up for further studies. In silico analysis revealed that all ESTs were linked with the HSP family. Gene Ontology (GO) analysis revealed that the deduced protein sequences of the heat-linked 24 ESTs were involved in various biological pathways regulating heat stress response. Hydropathy analysis revealed that all protein sequences were hydrophilic in nature. Based on the phylogenetic analysis, all HSP-related protein sequences were divided into seven groups. Analysis of cis-elements provides molecular evidence for the possible involvement of hydrophilic ESTs in the process of abiotic stress tolerance in sorghum. Based on these results, it was suggested that putative ESTs may play an important role in heat stress tolerance.
    No preview · Article · Dec 2015 · International Journal of Bioinformatics Research and Applications
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    ABSTRACT: Protein complexes are key molecular entities that perform a variety of essential cellular functions. The connectivity of proteins within a complex has been widely investigated with both experimental and computational techniques. We developed a computational approach to identify and characterise proteins that play a role in interconnecting complexes. We computed a measure of inter-complex centrality, the crossroad index, based on disjoint paths connecting proteins in distinct complexes and identified inter-complex hubs as proteins with a high value of the crossroad index. We applied the approach to a set of stable complexes in Saccharomyces cerevisiae and in Homo sapiens. Just as done for hubs, we evaluated the topological and biological properties of inter-complex hubs addressing the following questions. Do inter-complex hubs tend to be evolutionary conserved? What is the relation between crossroad index and essentiality? We found a good correlation between inter-complex hubs and both evolutionary conservation and essentiality.
    No preview · Article · Dec 2015 · International Journal of Bioinformatics Research and Applications
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    ABSTRACT: Currently, internet is the best tool for distributed computing, which involves spreading of data geographically. But, retrieving information from huge data is critical and has no relevance unless it provides certain information. Prediction of missing associations can be viewed as fundamental problems in machine learning where the main objective is to determine decisions for the missing associations. Mathematical models such as naive Bayes structure, human composed network structure, Bayesian network modelling, etc., were developed to this end. But, it has certain limitations and failed to include uncertainties. Therefore, effort has been made to process inconsistencies in the data with the introduction of rough set theory. This paper uses two processes, pre-process and post-process, to predict the decisions for the missing associations in the attribute values. In preprocess, rough set is used to reduce the dimensionality, whereas neural network is used in postprocess to explore the decision for the missing associations. A real-life example is provided to show the viability of the proposed research.
    No preview · Article · Dec 2015 · International Journal of Bioinformatics Research and Applications
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    ABSTRACT: We describe an automatic segmentation method for polyproteins of the viruses belonging to the Potyviridae family. It uses machine learning techniques in order to predict the cleavage site which define the segments in which said polyproteins are cut in their process of functional maturation. The segmentation application is publicly available for use on a website and it can be accessed through the web service interface too. The prediction models have an average sensitivity of 0.79 and a Matthews correlation coefficient average of 0.23. This method is capable of predicting correctly (coinciding with previously published segmentation) the segmentation of sequences which come from Potyvirus and Rymovirus, genera. However accurate prediction capabilities are affected when faced with either atypical sequences or viruses belonging to less common genera in the Potyviridae family. Future work will focus on establishing greater flexibility in this sense.
    No preview · Article · Dec 2015 · International Journal of Bioinformatics Research and Applications
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    ABSTRACT: The human gut is one of the most densely populated microbial communities in the world. The interaction of microbes with human host cells is responsible for several disease conditions and of criticality to human health. It is imperative to understand the relationships between these microbial communities within the human gut and their roles in disease. In this study we analyse the microbial communities within the human gut and their role in Inflammatory Bowel Disease (IBD). The bacterial communities were interrogated using Length Heterogeneity PCR (LH-PCR) fingerprinting of mucosal and luminal associated microbial communities for a class of healthy and diseases patients.
    No preview · Article · Mar 2015 · International Journal of Bioinformatics Research and Applications
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    ABSTRACT: The incidence of bacterial disease has increased tremendously in the last decade, because of the emergence of drug resistance strains within the bacterial pathogens. The present study was to investigate the antibacterial compound 2,5-di-tert-butyl-1,4-benzoquinone (DTBBQ) isolated from marine Streptomyces sp. VITVSK1 as a potent antibacterial agent. The antibacterial potential of DTBBQ was investigated against RNA Polymerase (PDB ID-1I6V) by in silico molecular docking tools. Results of our study showed the high affinity interaction between DTBBQ and RNA polymerase and also confirmed the drug likeliness of DTBBQ using ADMET in silico pharmacology tools. Our findings suggest that DTBBQ could be used as antibacterial drug to defend the emerging antibacterial resistance.
    No preview · Article · Mar 2015 · International Journal of Bioinformatics Research and Applications
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    ABSTRACT: Investigation of essential proteins is significantly valuable for understanding of cellular life, drug design and other practical purposes. In most of current studies, essential proteins are generally mined in protein-protein interaction (PPI) networks with diverse topology features. In this study, we investigate what kind of proteins is inclined to be essential from a new perspective. The investigation implies that protein essentiality is correlated with protein domains, which are functional, structural and evolutionary units of proteins. Proteins with a larger Number of Domain Types (NDT) tend to be essential. The analyses on 22 species show that essential proteins identified by NDT are much more than those identified by ten random identifications. The consideration of the structural feature makes us less dependent on network data and thus enables us to investigate protein essentiality of more species with incomplete and/or inconsistent network data.
    No preview · Article · Mar 2015 · International Journal of Bioinformatics Research and Applications
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    ABSTRACT: Hepatitis Delta Virus (HDV) is an RNA virus and causes delta hepatitis in humans. Although a lot of data is available for HDV, but retrieval of information is a complicated task. Current web database 'HDVDB' provides a comprehensive web-resource for HDV. The database is basically concerned with basic information about HDV and disease caused by this virus, genome structure, pathogenesis, epidemiology, symptoms and prevention, etc. Database also supplies sequence data and bibliographic information about HDV. A tool 'siHDV Predict' to design the effective siRNA molecule to control the activity of HDV, is also integrated in database. It is a user friendly information system available at public domain and provides annotated information about HDV for research scholars, scientists, pharma industry people for further study.
    No preview · Article · Mar 2015 · International Journal of Bioinformatics Research and Applications
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    ABSTRACT: Bio-systems are inherently complex information processing systems. Their physiological complexities limit the formulation and testing of a hypothesis for their behaviour. Our goal here was to test a computational framework utilising published data from a longitudinal study of patients with acute myeloid leukaemia (AML), whose DNA from both normal and malignant tissues were subjected to NGS analysis at various points in time. By processing the sequencing data before relapse time, we tested our framework by predicting the regions of the genome to be mutated at relapse time and, later, by comparing our results with the actual regions that showed mutations (discovered by genome sequencing at relapse time). After a detailed statistical analysis, the resulting correlation coefficient (degree of matching of proposed framework with real data) is 0.9816 ± 0.009 at 95% confidence interval. This high performance from our proposed framework opens new research opportunities for bioinformatics researchers and clinical doctors.
    No preview · Article · Jan 2015 · International Journal of Bioinformatics Research and Applications
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    ABSTRACT: A Probabilistic Neural Network (PNN) is a statistical algorithm and consists of a grouping of multi-class data. The conventional method of detection of DNA mutations by the human eye may not detect the minute variations in PCR-SSCP bands, which may lead to false positive or false negative results. The detection by photographic images may contain a blare (noise) caused during the time of photography; therefore, image processing techniques were used to reduce image noise. PCR-SSCP gels of T2DM patients (n = 100) and controls (n = 100) were initially photographed with equal ratio of pixels and later subjected to a two-stage analysis: feature extraction and PNN. The evaluation of the results was done by quality training and the accuracy was up to 95%, and the human eye analysis showed 80% mutation detection rate. This study proves to be very reliable and gives accurate and fast detection for mutation analysis in diabetes. This method could be extended for analysis in other human diseases.
    No preview · Article · Jan 2015 · International Journal of Bioinformatics Research and Applications
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    ABSTRACT: Class B GPCR family is a small group of receptors which are activated by peptides of intermediate length that range from 30 to 40 amino acid residues including hormones, neuropeptides and autocrine factors that mediate diverse physiological functions. They are involved in physiological processes like glucose homeostasis (glucagon and glucagon-like peptide-1), calcium homeostasis and bone turnover (parathyroid hormone and calcitonin), and control of the stress axis (corticotropin-releasing factor). Most of the GPCR structures and their functions are still unknown. Thus, the study of amino acid association patterns can be useful in prediction of their structure and functions. In view of above, in this paper, an attempt has been made to explore amino acid association patterns in class B GPCRs and their relationships with secondary structures and physiochemical properties. The fuzzy association rule mining is employed to take care of uncertainty due to variation in length of sequences. The association rules have been generated with the help of patterns discovered in the sequences.
    No preview · Article · Jan 2015 · International Journal of Bioinformatics Research and Applications
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    ABSTRACT: Design of selective matrix metalloproteinases (MMPs) inhibitors is still a challenging task because of binding pocket similarities and flexibility among MMPs family. To overcome this issue we try to generate a (threedimensional quantitative structure activity relationship) 3D-QSAR model that might reflect, at least in part, the differential properties of MMP-12 and MMP-13 active sites compared to each other. The different alignment rules were applied for CoMFA/CoMSIA model development. In an approach the best docked poses were followed by alignment based on their zinc binding group. As it was suggested by comparison of CoMSIA contour maps of MMP-12 with MMP-13, the ligand based approach can find more detailed features of specificity for MMPs that have similar highly flexible active sites, than solely analysis of available crystal structures. The residues Val194, Leu214 and Thr220 of MMP-13 were suggested to be investigated for flexibility upon binding of different ligands.
    No preview · Article · Jan 2015 · International Journal of Bioinformatics Research and Applications