1. WMU CS6260 Parallel Computations II Spring 2013 Presentation #2 Professor: Dr. de Doncker Name: Xuanyu Hu March/11/2013

2.  Quick Review About Last Presentation  More Details  Genbank  The Beginning Of Bioinformatics  How to use genbank  Problems  Good Performance In Bioinformatics  The Results From Real DNA  The Results Of Our Project  Future  Conclusion  Nothing Is Impossible  Questions  References

3.  Quick Review About Last Presentation  More Details  Genbank  The Beginning Of Bioinformatics  How to use genbank  Problems  Good Performance In Bioinformatics  The Results From Real DNA  The Results Of Our Project  Future  Conclusion  Nothing Is Impossible  Questions  References

4.  Pattern in DNA  Function  Drug target identification and new drug discovery

6.  Solution in a Sequential Way  Greedy Algorithm  Brute Force  Branch And Bound  Parallelize the serial program with MPI  Loading balance in parallel program

7.  Quick Review About Last Presentation  More Details  Genbank  The Beginning Of Bioinformatics  How to use genbank  Problems  Good Performance In Bioinformatics  The Results From Real DNA  The Results Of Our Project  Future  Conclusion  Nothing Is Impossible  Questions  References

8.  Over the past decade there has been a dramatic increase in the number of completely sequenced genomes resulting from the race of multibillion-dollar genome-sequencing projects.

9. The results of these achievements have led to a flood of data in genome sequence databases such as Genbank and EMBL, which has caused them to double in size almost every year.

10.  Quick Review About Last Presentation  More Details  Genbank  The Beginning Of Bioinformatics  How to use genbank  Problems  Good Performance In Bioinformatics  The Results From Real DNA  The Results Of Our Project  Future  Conclusion  Nothing Is Impossible  Questions  References

11.  This flood of sequence data requires a system of representing, organising, manipulating, distributing, maintaining and finally using the information (Computer Simulation).  Bioinformatics(bridge)  Computer Science work with Biology  Computer Science work for Biology

12.  Quick Review About Last Presentation  More Details  Genbank  The Beginning Of Bioinformatics  How to use genbank  Problems  Good performance In Bioinformatics  The Results From Real DNA  The Results Of Our Project  Future  Conclusion  Nothing Is Impossible  Questions  References

14. Example: Protein consensus pattern to DNA RegEx

15.  Quick Review About Last Presentation  More Details  Genbank  The Beginning Of Bioinformatics  How to use genbank  Problems  Good Performance In Bioinformatics  The Results From Real DNA  The Results Of Our Project  Future  Conclusion  Nothing Is Impossible  Questions  References

16.  More and more DNA sequence  Not enough memory for DNA sequence  If we don’t have the super- computer with lots of processors  Can I find the results with normal computers with the same performance of parallel computation?

17.  Quick Review About Last Presentation  More Details  Genbank  The Beginning Of Bioinformatics  How to use genbank  Problems  Good Performance In Bioinformatics  The Results From Real DNA  The Results Of Our Project  Future  Conclusion  Nothing Is Impossible  Questions  References

21.  Quick Review About Last Presentation  More Details  Genbank  The Beginning Of Bioinformatics  How to use genbank  Problems  Good Performance In Bioinformatics  The Results From Real DNA  The Results Of Our Project  Future  Conclusion  Nothing Is Impossible  Questions  References

22. N = 55, T = 20, L = 9

23.  Quick Review About Last Presentation  More Details  Genbank  The Beginning Of Bioinformatics  How to use genbank  Problems  Good Performance In Bioinformatics  The Results From Real DNA  The Results Of Our Project  Future  Conclusion  Nothing Is Impossible  Questions  References

24.  A far more practical and effective approach incorporates the usage of parallel clusters of workstations.  Cloud Computing

25.  Quick Review About Last Presentation  More Details  Genbank  The Beginning Of Bioinformatics  How to use genbank  Problems  Good Performance In Bioinformatics  The Results From Real DNA  The Results Of Our Project  Future  Conclusion  Nothing Is Impossible  Questions  References

26.  Details about Parallel Motif Finding Algorithms for Bioinformatics  Quick Review About Last Presentation  More Details  Genbank  The Beginning Of Bioinformatics  How to use genbank  Problems  Good Performance In Bioinformatics  The Results From Real DNA  The Results Of Our Project  Future(Solution for problems)  Download  Transformation  Find the Pattern  Bioinformatics give the information biologists need

28.  Quick Review About Last Presentation  More Details  Genbank  The Beginning Of Bioinformatics  How to use genbank  Problems  Good Performance In Bioinformatics  The Results From Real DNA  The Results Of Our Project  Future  Conclusion  Nothing Is Impossible  Questions  References

30.  Quick Review About Last Presentation  More Details  Genbank  The Beginning Of Bioinformatics  How to use genbank  Problems  Good Performance In Bioinformatics  The Results From Real DNA  The Results Of Our Project  Future  Conclusion  Nothing Is Impossible  Questions  References

32.  Quick Review About Last Presentation  More Details  Genbank  The Beginning Of Bioinformatics  How to use genbank  Problems  Good Performance In Bioinformatics  The Results From Real DNA  The Results Of Our Project  Future  Conclusion  Nothing Is Impossible  Questions  References

33.  http://eprints.ru.ac.za/162/1/Akhurst_MSc.pd f http://eprints.ru.ac.za/162/1/Akhurst_MSc.pd f  http://www.ncbi.nlm.nih.gov/gene/ http://www.ncbi.nlm.nih.gov/gene/