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Versteeg, R., van Schaik, B.D., van Batenburg, M.F., Roos, M., Monajemi, R., Caron, H., Bussemaker, H.J. and van Kampen, A.H. (2003) The Human Transcriptome Map Reveals Extremes in Gene Density, Intron Length, GC Content, and Repeat Pattern for Domains of Highly and Weakly Expressed Genes. Genome Research, 13, 1998-2004.
https://doi.org/10.1101/gr.1649303

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• TITLE: BioAnalyzer: Bioinformatic Software of Routinely Used Tools for Analysis of Genomic Data

  AUTHORS: Peter Tharwat Habib, Alsamman Mahmoud Alsamman, Aladdin Hamwieh

  KEYWORDS: Biopython, Bioinformatics, FASTA, Genbank, Multiple Sequence Alignment, BLAST, NCBI, Data Visualization

  JOURNAL NAME: Advances in Bioscience and Biotechnology, Vol.10 No.3, March 21, 2019

  ABSTRACT: The massive extension in biological data induced a need for user-friendly bioinformatics tools could be used for routine biological data manipulation. Bioanalyzer is a simple analytical software implements a variety of tools to perform common data analysis on different biological data types and databases. Bioanalyzer provides general aspects of data analysis such as handling nucleotide data, fetching different data formats information, NGS quality control, data visualization, performing multiple sequence alignment and sequence BLAST. These tools accept common biological data formats and produce human-readable output files could be stored on local computer machines. Bioanalyzer has a user-friendly graphical user interface to simplify massive biological data analysis and consume less memory and processing power. Bioanalyzer source code was written through Python programming language which provides less memory usage and initial startup time. Bioanalyzer is a free and open source software, where its code could be modified, extended or integrated in different bioinformatics pipelines. Bioinformatics Produce huge data in FASTA and Genbank format which can be used to produce a lot of annotation information which can be done with Python programming language that open the door form bioinformatics tool due to their elasticity in data analysis and simplicity which inspire us to develop new multiple tool software able to manipulate FASTA and Genbank files. The goal Develop new software uses Genomic data files to produce annotated data. Software was written using python programming language and biopython packages.