1. Siniša Ivković, Goran Rakočević, Prof. Veljko Milutinovic University of Belgrade School of Electrical Engineering

2. Introduction -Sequence alignment way of arranging sequences of DNK, RNK or protein to identify regions of similarity functional structural evolutionary relationships between sequences 2/13 - How to know that two genes, often in different organizams, in fact two versions of the same gene? Similarity! Siniša Ivković - sinisa.ivkovic@gmail.com

3. There are a number of algorithms that solve problems of aligning the sequences and guarantee the best solutions By increasing amount of data that need to be processed execution speed of these algorithms becomes unacceptable Therefore, we must turn to heuristic methods - BLAST Introduction 3/13Siniša Ivković - sinisa.ivkovic@gmail.com

4. BLAST - Basic Local Alignment Search Tool Fast local sequence alignment algorithm BLAST efficiency lies in the fact that it tends to find regions of high similarity, not necessarily trying to find and check all local alignment. 4/13 KRKLQRNRTSFTQEQIEALEKEFERTHYPDVFARERLAAKIDLPEARIQVWFSNRRAKWRREEKL KKKHRRNRTTFTTYQLHQLERAFEASHYPDVYSREELAAKVHLPEVRVQVWFQNRRAKWRRQERL Siniša Ivković - sinisa.ivkovic@gmail.com

5. Parallel BLAST - Most bioinformatics algorithms are designed as a sequential The very nature of bioinformatics processing The rapid spread of knowledge in biology causes constant emergence of new concepts, and significant changes to already known - Declining price of genome sequencing requires increasing the speed of execution of these algorithms - Implementations of Parallel BLAST PThread MPI 5/13Siniša Ivković - sinisa.ivkovic@gmail.com

6. ETF Hadoop BLAST - Big Data – collection of data sets so large and complex that it becomes difficult to process using standard database tools or traditional data processing applications - Parallel computing – a form of computation in which many calculations are carried out simultaneously communication and synchronization between processes hardware failure - MapReduce – programming model that frees programmers of thinking about these problems - Apache Hadoop – free implementation of the MapReduce paradigm 6/13Siniša Ivković - sinisa.ivkovic@gmail.com

7. MapReduce MAP SORT VALUE REDUCE VALUE 7/13Siniša Ivković - sinisa.ivkovic@gmail.com

8. mySequence {q1} {db1} {db2} {db3} {q1} {db1} {q1} {db2} {q1} {db3} MAP {db1} {hit1} {db1} {hit2} {db2} {hit3} {db2} {hit4} {db3} {hit5} {db3} {hit6} ETF Hadoop BLAST - Implementation 8/13Siniša Ivković - sinisa.ivkovic@gmail.com

9. mySequence {q1} {db1} {db2} {db3} {q1} {db1} {q1} {db2} {q1} {db3} MAP {db1} {hit1} {db1} {hit2} {db2} {hit3} {db2} {hit4} {db3} {hit5} {db3} {hit6} REDUCE {db1}{db2} {db3} {hit1}{hit3} {hit6} ETF Hadoop BLAST - Implementation 9/13Siniša Ivković - sinisa.ivkovic@gmail.com

10. ETF Hadoop BLAST >GENSCAN00000000013 pep:genscan chromosome:GRCh37:18:4755977:4807982:1 transcript:GENSCAN00000000013 transcript_biotype:protein_coding TANTGLLAVKVEVIILVSLTHAQLSRAGQHAGCTTCLQDECAVAAGEEEETQQGELADVIYPSLL AASTSSVLEDGAGPHKGLQKLSRLIRFVDVVGGFRREKGYMAWIKPRYSEFPKVNSWTESSFP FG HSP: 661 E-value: 0.001446314485823671 10/13Siniša Ivković - sinisa.ivkovic@gmail.com

11. Conclusion - Bioinformatics has become an important part of many areas of biology Sequencing and annotating genomes and their observed mutations Datamining of biological literature and the development of gene ontologies Understanding of evolutionary aspects of molecular biology - Personalized medicine Medical model that proposes the customization of healthcare We need to consider whole spectar of clinical information Electronic health care records Clinical trials etc. 11/13Siniša Ivković - sinisa.ivkovic@gmail.com

12. Conclusion - We need to collect information from real world - Develop analytics that can actually extract causal relationships and generate predictive models - Future steps: - Specialized hardvare (FPGA) 12/13Siniša Ivković - sinisa.ivkovic@gmail.com

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