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Protein hot spots prediction
Kašpárek, Jan ; Tkacz, Ewaryst (referee) ; Maděránková, Denisa (advisor)
Knowledge of protein hot spots and the ability to successfully predict them while using only primary protein structure has been a worldwide scientific goal for several decades. This thesis describes the importance of hot spots and sums up advances achieved in this field of study so far. Besides that we introduce hot spot prediction algorithm using only a primary protein structure, based primarily on signal processing techniques. To convert protein sequence to numerical signal we use the EIIP attribute, while further processing is carried out via means of S-transform. The algorithm achieves sensitivity of more than 60 %, positive predictive value exceeds 50 % and the main advantage over competitive algorithms is its simplicity and low computational requirements.
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Hardware Acceleration of Algorithms for Approximate String Matching
Nosek, Ondřej ; Kořenek, Jan (referee) ; Martínek, Tomáš (advisor)
Methods for aproximate string matching of various sequences used in bioinformatics are crucial part of development in this branch. Tasks are of very large time complexity and therefore we want create a hardware platform for acceleration of these computations. Goal of this work is to design a generalized architecture based on FPGA technology, which can work with various types of sequences. Designed acceleration card will use especially dynamic algorithms like Needleman-Wunsch and Smith-Waterman.
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Hardware Acceleration of Algorithms for Approximate String Matching
Nosek, Ondřej ; Kořenek, Jan (referee) ; Martínek, Tomáš (advisor)
Methods for aproximate string matching of various sequences used in bioinformatics are crucial part of development in this branch. Tasks are of very large time complexity and therefore we want create a hardware platform for acceleration of these computations. Goal of this work is to design a generalized architecture based on FPGA technology, which can work with various types of sequences. Designed acceleration card will use especially dynamic algorithms like Needleman-Wunsch and Smith-Waterman.
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Protein hot spots prediction
Kašpárek, Jan ; Tkacz, Ewaryst (referee) ; Maděránková, Denisa (advisor)
Knowledge of protein hot spots and the ability to successfully predict them while using only primary protein structure has been a worldwide scientific goal for several decades. This thesis describes the importance of hot spots and sums up advances achieved in this field of study so far. Besides that we introduce hot spot prediction algorithm using only a primary protein structure, based primarily on signal processing techniques. To convert protein sequence to numerical signal we use the EIIP attribute, while further processing is carried out via means of S-transform. The algorithm achieves sensitivity of more than 60 %, positive predictive value exceeds 50 % and the main advantage over competitive algorithms is its simplicity and low computational requirements.
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