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International Journal of Biomedical Data Mining
Open Access

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Journal Impact Factor 0.2*
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About the Journal

The International Journal of Biomedical Data Mining (JBDM) is a scholarly open access, peer-reviewed, and fully refereed journal which publishes articles on valuable algorithms, methods and software tools encompassing the arena of data mining, knowledge discovery, data analysis and machine learning techniques and their applications in biomedical, healthcare and bioinformatics problems. Contributions are welcome from different disciplines such as computer science, engineering, statistics, biomedical informatics, general sciences and mathematics.

Articles presenting original research in the field, highlighting methodological aspects and providing experimental evidences on specific problems and all aspects of data mining applied to high-dimensional biological and biomedical data are expected for publishing in this periodical. This Journal acknowledges the inter-disciplinary nature of research in biological data mining and bioinformatics and provides a unified forum for researchers, scientists, students, policy makers to share the latest research and developments in this fast growing multi-disciplinary research area. Comprehensive review articles, short communications, technical notes and book and software reviews are also welcome.

The Journal is using Editor Manager System for smooth functioning of the peer review process and acceptance of any citable article depends on at least two independent outside reviewers comment followed by Editor's discretion.

Bioinformatics

Bioinformatics is the application of computer technology to the management of biological information. Computers are used to gather, store, analyze and integrate biological and genetic information which can then be applied to gene-based drug discovery and development. Bioinformatics tools aid in the comparison of genetic and genomic data and more generally in the understanding of evolutionary aspects of molecular biology. At a more integrative level, it helps analyze and catalogue the biological pathways and networks that are an important part of systems biology. In structural biology, it aids in the simulation and modeling of DNA, RNA, and protein structures as well as molecular interactions.

Related Journals: Bioinformatics and data mining, International journal of data ware house, Proteomics & Bioinformatics, Bioinformatics, Proteins: Structure, Function and Genetics, BMC Bioinformatics, Briefings in Bioinformatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics

Biomedical

Biomedical involves the application of the natural sciences, especially the biological and physiological sciences, to clinical medicine. It is a discipline that advances knowledge in engineering, biology and medicine and improves the human health through cross disciplinary activities that integrate the engineering sciences with biomedical sciences and clinical practices.

Related Journals: Data mining in health care, Data mining in clinical data base, International Journal of Biomedical Data Mining, Biomedical Sciences, Journal of Biomedical Engineering and Medical Devices, Diagnostic Techniques & Biomedical Analysis, Bioengineering & Biomedical Science, Journal of Biomedical Optics, Annals of Biomedical Engineering, Journal of Biomedical Informatics, Annual Review of Biomedical Engineering, Journal of Biomedical Materials Research

Computational Biology

Computational biology is the application of computer science, statistics, and mathematics to problems in biology. Computational biology spans a wide range of fields within biology, including genomics/genetics, biophysics, cell biology, biochemistry, and evolution. Likewise, it makes use of tools and techniques from many different quantitative fields, including algorithm design, machine learning, Bayesian and frequents statistics and statistical physics.

Related Journals: International journal of data mining in bioinformatics, International journal of biomedical data mining, PLoS Computational Biology, Journal of Computational Biology, Computational Biology and Chemistry, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Journal of Bioinformatics and Computational Biology, International Journal of Computational Biology and Drug Design

Data Analysis

Data Analysis is the process of systematically applying statistical and/or logical techniques to describe and illustrate, condense and recap, and evaluate data. Data analytics is used in many industries to allow companies and organization to make better business decisions and in the sciences to verify or disprove existing models or theories.

Related Journals: Data mining research, International journal of data mining in bioinformatics, Computational Statistics and Data Analysis, Intelligent Data Analysis, Lifetime Data Analysis, Advances in Adaptive Data Analysis, Advances in Data Analysis and Classification, International Journal of Data Analysis Techniques and Strategies

Data Mining

Data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases.

Related Journals: Data mining models, Statistical analysis and data mining, International Journal of Biomedical Data Mining, Data Mining in Genomics & Proteomics, Informatics and Data Mining, BioData Mining, International Journal of Data Mining and Bioinformatics, Statistical Analysis and Data Mining, Data Mining and Knowledge Discovery, International Journal of Data Mining, Modelling and Management

Epidemiological Data Analysis

Epidemiology data represents the abundance of a particular pathogenic organism in a specific geographical region. Analysis of such data along with the impact of various important factors such as climatic and geographical factors, alteration of behavior of the pathogen and the host or the carrier of the pathogen is mandatory in such issues. Advanced computation and statistical means are the ways to analyze such important data and predict the future aspects of the disease epidemics.

Related Journals: Data mining in clinical data base, Statistical analysis of data mining with impact factor, American Journal of Epidemiology, Journal of Clinical Epidemiology, Epidemiology, Epidemiology and Infection, Genetic Epidemiology

Genome Data Mining

Data mining impacted the present era of information retrieval system from a heap of data. Irrespective of the data, advanced mining techniques provide the essence of the datasets and extract the pattern of data. Next generation sequencing techniques generated a large pool of information from the genomes of several important organisms. Analysis of the genome data through mining has provided a tool to us for retrieval of the true meaning of the information and also to reduce the noise in the generated information.

Related Journals: Data mining in marketing, Bioinformatics and data mining, International Journal of Biomedical Data Mining, Data Mining in Genomics & Proteomics, Informatics and Data Mining, Genome Research, Genome Biology, Genome, Genome Biology and Evolution, Advances in Genome Biology

In silico Analysis

Computational analyses gained momentum after the human genome project and it proved its importance in analyzing biological information. Apart from in vivo and in vitro methodologies in silico techniques are popular among the scientific community in generating reliable scientific information based on the requirement of data analysis.

Related Journals: International journal of data mining in bioinformatics, Data mining magazine, Bioanalysis & Biomedicine, Journal of Proteomics and Bioinformatics, Diagnostic Techniques & Biomedical Analysis, Journal of Clinical Bioinformatics,  Applied Bioinformatics, BMC Bioinformatics, Journal of Bioinformatics and Computational Biology

Medical Devices

Medical devices are of different types, some are used for monitoring and some are used for diagnostics purposes. In both the cases they are useful and being used for the urgent medical need.

Related Journals: Data mining in clinical data base, Mining research, Advances in Weight Loss Management & Medical Devices, Journal of Biomedical Engineering and Medical Devices, Expert Review of Medical Devices, Journal of Medical Devices, Transactions of the ASME, Medical Devices: Evidence and Research, Open Medical Devices Journal

Sequence analysis

Sequence analysis is a branch of Bioinformatics which encompasses the analysis of the generated genes, proteins or genome sequences belonging to any organism. Sequence analysis techniques uses mathematical modeling methods such as Hidden Markov Models (HMM), DSSP, position specific scoring matrices (PSSM) to analyze a pattern hidden in a particular sequence.

Related Journals: Statistical analysis of data mining with impact factor, International journal of data mining in bioinformatics, Journal of Integer Sequences, Recent Patents on DNA and Gene Sequences, Advances in DNA Sequence-Specific Agents

Medical Informatics

Medical Informatics is defined by the use of informatics and associated applications for relevant medical purpose. This includes programming for medical devices or other biomedical purposes, development of relevant databases for general or medical use, specific informatics based pipe line development to solve a particular medical problem.

Related Journals: Statistical analysis and data mining, Data mining in health care, Clinical & Medical Biochemistry: Open Access, Bioengineering & Biomedical Science, Clinical & Medical Genomics, International Journal of Biomedical Data Mining, Journal of the American Medical Informatics Association : JAMIA, International Journal of Medical Informatics, Journal of Biomedical Informatics, BMC Medical Informatics and Decision Making, Japan Journal of Medical Informatics, Applied Medical Informatics

Protein sequencing

Protein molecules are structural and functional component of a cellular environment. Estimation of the quantity of proteins has been a routine process in scientific community and academics. Sequencing of proteins unveiled the mysteries of proteins and aided in understanding the complex structural and functional phenomena of protein networks and cascading events. Several methods are used for protein sequencing which contains enzyme based methods, mass spectrometry based methods and automated sequencing methods.

Related Journals: Data mining journal with impact factor, International journal of data mining, Proteins: Structure, Function and Genetics, Protein Science, Protein Engineering, Design and Selection, Protein Journal, Protein and Cell

System Biology

System biology represents the analysis of an organization cascading physiological or biochemical events through experimentation and computational methods. System biology includes large scale experimentation or computational techniques including system representation in an in silico framework and analyzing and visualizing a real time cellular event which may use system biology mark up (SBML) language or other sophisticated and advanced technology.

Related Journals: Data mining in marketing, International journal of data ware house, EURASIP Journal on Bioinformatics and System Biology, Journal of Computer Science & Systems Biology, BMC System Biology,Advances in System Biology, Genome Biology, Genome

Protein Structure prediction

Structural prediction of protein molecules involves analysis of the secondary, tertiary and quaternary component of a protein. Stereo chemical assessment and other aspect can be evaluated in a cost effective manner.

Related Journals: Data mining in clinical data base, Data mining models, Proteins: Structure, Function and Genetics, Biochimica et Biophysica Acta - Proteins and Proteomics, Probiotics and Antimicrobial Proteins, Amino Acids, Peptides and Proteins

Proteomics

Proteomics refers to the analysis of the whole proteome for a particular organism. This includes experimental and theoretical techniques.

Related Journals:  Data mining magazine, Statistical analysis and data mining, Data Mining in Genomics & Proteomics, Proteomics & Bioinformatics, Molecular and Cellular Proteomics, Proteomics, Journal of Proteomics, Proteomics Research Journal

Biomedical data mining

Biomedical data mining refers to the analysis of the data generated for a solution of a biomedical problem. Advanced computational methodologies are in general applied for data mining purpose.

Related Journals: Data mining journal with impact factor, Data mining research, International Journal of biomedical DataMining, International Journal of Data Mining and Bioinformatics, Data Mining and Knowledge Discovery, BioData Mining, IEEE Transactions on Biomedical Engineering, Journal of Biomedical Informatics, Journal of Biomedical Science

Biostatistics and Clinical Informatics

Biostatistics is an interdisciplinary branch of mathematics and statistics where problems are considered from biology. Application of statistical measures is crucial for several important decision and classification purposes. Clinical informatics applies the advanced statistical implementations for solving the issues based on ample amount of clinical data generated for different diseases.

Related Journals: International journal of biomedical data mining, International journal of data mining in bioinformatics, Biometrics & Biostatistics, Biostatistics, International Journal of Biostatistics, Journal of Epidemiology and Biostatistics, Clinical Chemistry, Clinical Cancer Research, Molecular Informatics, Journal of Biomedical Informatics

* 2015 Journal Impact Factor was established by dividing the number of articles published in 2013 and 2014 with the number of times they are cited in 2015 based on Google search and the Scholar Citation Index database. If 'X' is the total number of articles published in 2013 and 2014, and 'Y' is the number of times these articles were cited in indexed journals during 2015 then, impact factor = Y/X

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