WEB BASED PROGRAM FOR BIG MOLECULAR DATA CONVERSION FOR ANALYSIS BY MATLAB, PHYTON OR R

Year 2018, Volume: 2 Issue: 1, 27 - 31, 01.07.2018

Halit Hami Oz , Mahmut Aydın

Abstract

Molecular data is created in different formats: MICROSAT, SNP, AFLP, RFLP, DNA, RNA, DISTANCE, PROTEIN, DART, INDEL, RAPID. File formats includes Arlequin, Genpop, Structure, Nexus, Mega, Fasta. Scientists working in this field needs to analyze this molecular data, and he/she does it by either writing special programs to convert these big data to the format he needs or sends his/her data to some centers for analysis. User friendly and easy to use web based molecular data converting program was deveopled using R programming language at Kafkas University Department of Bioengineering and Department of Computer Engineering. Users can upload their data using the Web based program selecting input and out file formats to convert their big molecular data to the format they want for analysis using either R, Phyton programming languages or MATLAB Wavelet Toolbox™

Keywords

Matlab, Wavelet, Big Data, R, Bioenformatics

MATLAB, PHYTON VEYA R KULLANARAK WEB TABANLI BÜYÜK MOLEKÜLER VERI DÖNÜŞÜM ANALIZI

Abstract

Moleküler veriler farklı formatlarda oluşturulur: MICROSAT, SNP, AFLP, RFLP, DNA, RNA, MESAFANT, PROTEİN, DART, INDEL, HIZLI. Dosya biçimleri arasında Arlequin, Genpop, Structure, Nexus, Mega, Fasta bulunur. Bu alandaki bilim adamları bu moleküler veriyi analiz etmek ve bu büyük veriyi ihtiyaç duyduğu biçime dönüştürmek için özel programlar yazarak ya da verilerini analiz için bazı merkezlere göndererek yapar. Kullanıcı dostu ve kullanımı kolay web tabanlı moleküler veri dönüştürme programı, Kafkas Üniversitesi Biyomühendislik ve Bilgisayar Mühendisliği Bölümü’nde R programlama dili kullanılarak geliştirilmiştir. Kullanıcılar, giriş ve çıkış dosya formatlarını seçen Web tabanlı programı kullanarak veriler yükleyebilirler ve R programlama dili veya MATLAB Wavelet Toolbox kullanarak verilerini analiz edebilirler.

Keywords

Matlab, Wavelet, Big Data, R, Bioenformatics

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