Biological Data Mining (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
Language: English
Pages: 733
ISBN: 1420086847
Format: PDF / Kindle (mobi) / ePub
Like a data-guzzling turbo engine, advanced data mining has been powering post-genome biological studies for two decades. Reflecting this growth, Biological Data Mining presents comprehensive data mining concepts, theories, and applications in current biological and medical research. Each chapter is written by a distinguished team of interdisciplinary data mining researchers who cover state-of-the-art biological topics.
The first section of the book discusses challenges and opportunities in analyzing and mining biological sequences and structures to gain insight into molecular functions. The second section addresses emerging computational challenges in interpreting high-throughput Omics data. The book then describes the relationships between data mining and related areas of computing, including knowledge representation, information retrieval, and data integration for structured and unstructured biological data. The last part explores emerging data mining opportunities for biomedical applications.
This volume examines the concepts, problems, progress, and trends in developing and applying new data mining techniques to the rapidly growing field of genome biology. By studying the concepts and case studies presented, readers will gain significant insight and develop practical solutions for similar biological data mining projects in the future.
Building a Recommendation System with R
Agent-Based Semantic Web Service Composition (SpringerBriefs in Electrical and Computer Engineering)
Digital Media Processing: DSP Algorithms Using C
Watson-Crick base pairs. Biochemistry 37:14719–14735. [9] Xu, X., Yongmei, J., Stormo, G.D. 2007. RNA Sampler: a new sampling based algorithm for common RNA secondary structure prediction and structural alignment. Bioinformatics 23:1883–1891. [10] Giegerich, R., Voss, B., Rehmsmeier, M. 2007. Abstract shapes of RNA. Nucleic Acids Res. 32:4843–4851. [11] Steffen, P., Voss, B., Rehmsmeier, M., Reeder, J., Giegerich, R. 2006. RNAshapes: an integrated RNA analysis package based on abstract shapes.
Candidates, are performed as follows. The operation join merges four frequent triplets (α12 ; α13 , α23 ), (α23 ; α24 ; α34 ), (α13 , α14 ; α34 ) and (α12 ; α14 ; α24 ) into the candidate sextuple (α12 ; α13 ; α23 ; α24 ; α34 ; α14 ). In other words, four triplets are merged if the last angle of the first triplet is the same as the first angle of the second; the second element of the first triplet is the same as the first element of the third triplet, and so on. 42 Biological Data Mining The.
3 1 2 2 3 3 2 α2 3 7 3 6 2 6 3 6 7 3 α3 7 8 7 7 7 7 6 7 7 7 α4 8 8 8 8 8 8 8 8 8 7 α5 9 9 8 9 9 9 9 9 8 8 Frequency 6,439 5,780 5,586 5,100 4,657 4,437 4,085 3,884 3,831 3,728 patterns in Table 2.5b are in almost all cases the same patterns detected as over-represented by comparison with the random sets. Over-represented patterns tend to be arranged into specific spatial conformations that can be described in terms of groups of parallel and anti-parallel 44 Biological Data Mining TABLE.
8.4). 170 Biological Data Mining FIGURE 8.4: Weak join within an assembly. The region highlighted by the box is not spanned by any mate-pair highlighting a possible misjoin. Finally several packages are available that allow a manual qualitative analysis of mate-pair consistency. These include consed [12], BACCardI [3], and Hawkeye [29]. Note that Hawkeye directly integrates with the amosvalidate pipeline allowing for the simultaneous examination of multiple types of misassembly signatures.
Gen frag dist 14,000 12,000 25,000 10,000 20,000 8000 15,000 6000 10,000 4000 100 150 200 250 300 350 Genome2 (4M) frag dist 14,000 30,000 50 2000 5000 0 0 (g) 40,000 0 200 400 600 800 1000 Genome3 (4M) pattern dist 35,000 0 (h) 16,000 Genome3 (4M) frag dist 14,000 30,000 12,000 25,000 10,000 20,000 8000 15,000 6000 10,000 4000 5000 2000 50 100 150 200 250 300 350 0 0 0 200 400 600 800 1000 0 50 100 150 200 250 300 350 FIGURE 8.5: Comparison of.