ePrints.FRI - University of Ljubljana, Faculty of Computer and Information Science

Predicting protein-RNA interaction sites on RNA

Aleks Huč (2015) Predicting protein-RNA interaction sites on RNA. MSc thesis.

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    The main goal of the master's thesis has been to develop prediction models for interactions between RNA and proteins. We have chosen hidden Markov models as our method for modelling and predicting interactions. From our initial data we have extracted representative features and motifs, which we used for building separate models for each experiment. Majority of proteins bind to the same or very similar features and motifs. We have compared the predictive accuracy of models build with two (presence of interaction) and three states (presence and intensity of interaction). Results show that models with two states perform better than models with three states. Merging predictions of multiple single experiment models in combined models, does not improve prediction accuracy. However, combined models perform with high accuracy, and can be used to determine the relations between proteins, such as competition, cooperation and independence with other proteins when interacting with RNA. We have presented hidden Markov models as viable method for predicting interactions between RNA and proteins.

    Item Type: Thesis (MSc thesis)
    Keywords: hidden Markov model, Markov chain, Viterbi algorithm, forward algorithm, backward algorithm, posterior decoding, transcription, RNA, protein, gene
    Number of Pages: 94
    Language of Content: Slovenian
    Mentor / Comentors:
    Name and SurnameIDFunction
    doc. dr. Tomaž Curk299Mentor
    Link to COBISS: http://www.cobiss.si/scripts/cobiss?command=search&base=51012&select=(ID=1536460483)
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Item ID: 3014
    Date Deposited: 20 Jul 2015 11:15
    Last Modified: 14 Sep 2015 13:59
    URI: http://eprints.fri.uni-lj.si/id/eprint/3014

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