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Discussion on Exact Match Algorithms: Hashing vs Binary Trees in Bioinformatics

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In this discussion, we explore algorithms for exact matches in bioinformatics, focusing on Hashing and Binary Trees. We analyze their complexities in real-world scenarios, specifically considering target sequences and query lengths in large genomic data sets. With an emphasis on performance, we compare O(mN) and O(m log N) complexities, where N is the target sequence length, m represents total query lengths, and discuss implications for genetic research involving millions of data pairs. We outline actionable tasks for ongoing projects, including disease modeling and genomic patterns.

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Discussion on Exact Match Algorithms: Hashing vs Binary Trees in Bioinformatics

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  1. 101 6,8-Mar Discussion of algorithms for exact matches Hashing, Binary trees a,c,g,t = 00, 01, 10, 11 log2(N)= 34 N=target sequence length e.g. 3E9 m=total of query lengths, E9 people * 30E9bp(5X) O(mN) vs O(mlogN) = E29 vs E21

  2. 101 6-Mar To do list draft 1. Mike: Bioweather HapMap 2. Chris Code HapMap-OMIM + PG processing 3. Resmi: Prob of disease lifetime NHS access 4. Kay: Regulatory elements conserved 5. Hettman: Modeling C sequestration Cyanob. SALP.model geographical – pump nutrients up. 6. Cynthia: Disease host coevol 7. Tiffany: Flu 1918 smRNA 1800 sequences TIGR. map 8. Deniz: Z^n(mod4) Clustering Metagene. Universal sequence library. 9. Xiaodi : image patterns UI find order 10. Katie: talk Broad. Anticip. GenePattern. Algorithms for string matching 11. Zach: environ allerg corr SNPs 500K Entrez compare with random admixture

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