Data-intensive Computing: Case Study Area 1: Bioinformatics B. Ramamurthy 6/17/20151

Human Genetics Genomics Human Genome project Proteomics Diseasome Tree of life project Phylogenetics 6/17/20152

Human cell Base pair of DNA: CG, AT – C – cytosine, G – guanine, A – adenine, T - thymine Each human cell contains approximately 3 billion base pairs. The DNA of a single cell contains so much information that if it were represented in printed words, simply listing the first letter of each base would require over 1.5 million pages of text! If laid end-to-end, the DNA strand measures about 2 – 3 meters. DNA is a single large molecule at the nucleus of cell It is coiled a double helix Each strand of the DNA molecule is made of A, C, G and T: example: AAAGTTCTTAATTA that will be matched on the other strand by the matching base: TTTCAAGAATTAAT These string of alphabets contain Ref: Ref text: Bioinformatics: Databases, tools and algorithms, by. O. Bosu and S.K. Thukral 6/17/20153

More details Sequence of base pairs are grouped to make sense: genes When a gene inside needs to be activated, the DNA molecule at the cell nucleus uncoils and unfurls to the right extent to expose that gene From the exposed ends of the DNA a RNA is formed. mRNA or messenger RNA is formed that carries with it the “print” of the open DNA section (Map process?) RNA and DNA differ in one respect: RNA does not contain T or thymine but it has uracil (U). RNA is short-lived (like intermediate data in MapReduce) Once mRNA is formed open sections of the DNA close off. 6/17/20154

Protein formation mRNA travels to the cytoplasm where it meets the ribosome (rRNA) Ribosome reads the code in the mRNA (codon) and form the amino acids. Twenty amino acids are prevalent in human cells. Ex: codon GCU GCC GCA correspond to alanine In effect ribosome is a process control computer that takes in as input codons and produces amino acids as output. Amino acids polymerize and form polypeptide chains called proteins Proteins fold and form the basic structures such as skin and hair. Even though brain controls major human functions at the cell level it the DNA that has the command and control. DNA is fixed code for a given human. (WORM characteristics) 6/17/20155

Life’s processes DNA is “program” that controls functions, operations and structure of a cell and in turn that of our life processes. Life processes are in fact dependent of the program in a DNA and the hundreds of millions of ribosomes. Life in this context appears as an immense distributed system. 6/17/20156

Bioinformatics Can we study, understand and analyze the complexity of the immensely complex system? It structure and programs? University of Arizona’s tree of life project (ToL): Human Genome project (NIH and DOE): collecting approximately 30,000 genes in human DNA and determining the sequences three billion bases that make up the human DNA. Out of the genes we do not know the functions of more than 50% of them. 99.9% of the nucleotide sequence is same for all of us 0.1% is attributed to individual differences such as race, color of skin, disposition to diseases High throughput sequencing is generating ultra scale biological data: how to analyze this data? That is a data-intensive problem. 6/17/20157

Existing solutions? Traditional databases: store, retrieve, analyze and/or predict huge biological data Software tools for implementing algorithms, and developing applications for in-silico experiments Visualization tools, user interfaces, web accessibility for search through data Machine learning and data mining methodologies. 6/17/20158

Databases Taxonomy DB Genomics Sequence db Structure db Proteomic database (PDB) Micro-array db Expression db Enzyme db Disease db Molecular biology db 6/17/20159

Tools Data analysis tools – MySQL – Perl Prediction tools – Clustering Modeling tools – Surface prediction, predicting area of interest, protein-protein interaction Alignment tools 6/17/201510

How can we help? How can we leverage our knowledge of large scale data management to address bioinformatics problems? DC methods. Large number of tools and data: how we standardize the efforts so that they are complementary or repetitive? Cloud computing. 6/17/201511

6/17/ Text Mining vs Genetic Sequence Mining (Dot plot) CORRELATIONS R E L A T I O N S H I P ACTCTAGGAGTC G A T A A T T C G A T C