Molecular Biology and Genetics / Moleküler Biyoloji ve Genetik

Permanent URI for this collectionhttps://hdl.handle.net/11147/9

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2012 - 20174

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End date: 2019Department: search.filters.department.İzmir Institute of Technology. Computer Engineering

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Now showing 1 - 4 of 4
  • Editorial
    Citation - WoS: 2
    Computational Mirnomics - Integrative Approaches
    (Informationsmanagement in der Biotechnologie e.V. (IMBio e.V.), 2017) Hofestaedt, Ralf; Allmer, Jens; Schreiber, Falk; Sommer, Bjoern; Allmer, Jens; 04.03. Department of Molecular Biology and Genetics; 04. Faculty of Science; 01. Izmir Institute of Technology
    With this special issue on Computational miRNomics, we would like to start a new generation of publications in the Journal of Integrative Bioinformatics (JIB). From 2017 onwards, JIB will be published by De Gruyter which is one of the largest Open Access publishers in Germany with a long history. Established in 1918 with roots reaching even further back, the JIB editorial board decided that De Gruyter is the perfect partner to increase the level of professionalism for our publication processing and journal development.
  • Article
    Citation - WoS: 7
    Citation - Scopus: 5
    A Machine Learning Approach for Microrna Precursor Prediction in Retro-Transcribing Virus Genomes
    (Informationsmanagement in der Biotechnologie e.V. (IMBio e.V.), 2016) Saçar Demirci, Müşerref Duygu; Allmer, Jens; Toprak, Mustafa; Toprak, Mustafa; Allmer, Jens; 03.04. Department of Computer Engineering; 04.03. Department of Molecular Biology and Genetics; 03. Faculty of Engineering; 04. Faculty of Science; 01. Izmir Institute of Technology
    Identification of microRNA (miRNA) precursors has seen increased efforts in recent years. The difficulty in experimental detection of pre-miRNAs increased the usage of computational approaches. Most of these approaches rely on machine learning especially classification. In order to achieve successful classification, many parameters need to be considered such as data quality, choice of classifier settings, and feature selection. For the latter one, we developed a distributed genetic algorithm on HTCondor to perform feature selection. Moreover, we employed two widely used classification algorithms libSVM and random forest with different settings to analyze the influence on the overall classification performance. In this study we analyzed 5 human retro virus genomes; Human endogenous retrovirus K113, Hepatitis B virus (strain ayw), Human T lymphotropic virus 1, Human T lymphotropic virus 2, Human immunodeficiency virus 2, and Human immunodeficiency virus 1. We then predicted pre-miRNAs by using the information from known virus and human pre-miRNAs. Our results indicate that these viruses produce novel unknown miRNA precursors which warrant further experimental validation.
  • Article
    Citation - WoS: 30
    Citation - Scopus: 34
    Gddom: an Online Tool for Calculation of Dominant Marker Gene Diversity
    (Springer Verlag, 2017) Abuzayed, Mazen; El-Dabba, Nourhan; Frary, Anne; Doğanlar, Sami; Doğanlar, Sami; 04.03. Department of Molecular Biology and Genetics; 04. Faculty of Science; 01. Izmir Institute of Technology
    Gene diversity (GD), also called polymorphism information content, is a commonly used measure of molecular marker polymorphism. Calculation of GD for dominant markers such as AFLP, RAPD, and multilocus SSRs is valuable for researchers. To meet this need, we developed a free online computer program, GDdom, which provides easy, quick, and accurate calculation of dominant marker GD with a commonly used formula. Results are presented in tabular form for quick interpretation. © 2016, Springer Science+Business Media New York.
  • Conference Object
    Citation - Scopus: 1
    De Novo Markup Language, a Standard To Represent De Novo Sequencing Results From Ms/Ms Data
    (Institute of Electrical and Electronics Engineers Inc., 2012) Takan, Savaş; Allmer, Jens; Allmer, Jens; Takan, Savaş; 04.03. Department of Molecular Biology and Genetics; 03.04. Department of Computer Engineering; 03. Faculty of Engineering; 04. Faculty of Science; 01. Izmir Institute of Technology
    Proteomics is the study of the proteins that can be derived from a genome. For the identification and sequencing of proteins, mass spectrometry has become the tool of choice. Within mass spectrometry-based proteomics, proteins can be identified or sequenced by either database search or de novo sequencing. Both methods have certain advantages and drawbacks but in the long run we envision de novo sequencing to become the predominant tool. Currently, de novo sequencing results are stored in arbitrary file formats, depending on the developers of the algorithms. We identified this as a large and unnecessary obstacle while integrating results from multiple de novo sequencing algorithms. Therefore, we designed a standard file format for the representation of de novo sequencing results. We further developed an application programming interface since we identified the lack of proper APIs as another obstacle, introducing a needlessly high learning curve for developers. © 2012 IEEE.