Data mining Data mining Sequence information Mapping information
- Slides: 49
Data mining
Data mining • • • Sequence information Mapping information Phenotypic information Literature Prediction programs - Gene prediction Promotor prediction Functional prediction Structural prediction Variant annotation
http: //www. ncbi. nlm. nih. gov/
Genome browsers • ENSEMBL: http: //www. ensembl. org/index. html • UCSC : http: //genome. ucsc. edu/
http: //www. ensembl. org/index. html
Ensembl Tools
http: //genome. ucsc. edu/
Assembly converter
http: //dgv. tcag. ca/dgv/app/home
https: //decipher. sanger. ac. uk/
Genomic variant analysis • Genomic variants - Mutation: literature, HGMD, gene specific databases - Polymorphism: db. SNP, EVS, Ex. AC - Prediction programs
http: //www. ncbi. nlm. nih. gov/SNP/
http: //evs. gs. washington. edu/EVS/
Ex. AC (http: //exac. broadinstitute. org/)
Ex. AC
Kaviar: http: //db. systemsbiology. net/kaviar/
Kaviar: http: //db. systemsbiology. net/kaviar/
http: //sift. jcvi. org/
CFTR: p. N 1303 K
CFTR: p. N 1303 K
Polyphen http: //genetics. bwh. harvard. edu/pph 2/
Mutation Taster http: //www. mutationtaster. org/
But beware……!!!!! There are many examples of known pathogenic variants predicted to be benign and vice versa
Human Splicing Finder http: //www. umd. be/HSF/
Splice Site Prediction http: //www. fruitfly. org/seq_tools/splice. html
Splice finder programs Gene. Splicer http: //www. cbcb. umd. edu/software /Gene. Splicer/gene_spl. shtml Netgene http: //www. cbs. dtu. dk/services/Net Gene 2/
http: //scholar. google. be
Batch Annotators & Prioritization Gene Panel / Whole Exome Sequencing • Large amounts of variants (50 -50, 000) • Needed information for interpretation: • Location w. r. t. gene (intron/exon/splicing) • Effect on CDS (synonymous/stop-gain/frameshift/. . . ) • Severity of the effect • Function of gene w. r. t. phenotype Example Applications: w. ANNOVAR: http: //wannovar. usc. edu Seattle. Seq: http: //snp. gs. washington. edu/Seattle. Seq. Annotation 141/ VEP: http: //www. ensembl. org/Tools/VEP Variant. DB: http: //biomina. be/apps/variantdb e. Xtasy: http: //extasy. esat. kuleuven. be/ Exomiser: http: //www. sanger. ac. uk/science/tools/exomiser
VEP
Batch Annotators: w. Annovar
NCBI Ensembl UCSC Genatlas http: //www. ncbi. nlm. nih. gov/ http: //www. ensemble. org/index. html http: //genome. ucsc. edu/ http: //genatlas. medecine. univ-paris 5. fr/ Poly. Phen SIFT Mutation taster Splice prediction http: //genetics. bwh. harvard. edu/pph 2/ http: //sift. jcvi. org/ http: //www. mutationtaster. org/ http: //www. umd. be/HSF/ http: //www. fruitfly. org/seq_tools/splice. html http: //www. cbs. dtu. dk/services/Net. Gene 2/ DECIPHER https: //decipher. sanger. ac. uk/
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- Terjemahan
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- Strip mining before and after
- Difference between strip mining and open pit mining
- Text and web mining
- Information gain in data mining
- Nucleotide sequence vs amino acid sequence
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- Convolutional sequence to sequence learning
- Data reduction in data mining
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- Data reduction in data mining
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- Analitical cubism
- Descriptive mining of complex data objects
- Olap database
- Noisy data in data mining
- Data warehouse 3 tier architecture
- Markku roiha
- Data compression in data mining
- Introduction to data warehouse
- Data warehouse dan data mining
- Complex data types in data mining
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- Esi data mapping
- Sequence logo information content
- Unsupervised learning in data mining
- Motivation and importance of data mining
- Data mining concepts and techniques slides
- Query tools in data mining
- Pump it up: data mining the water table
- Sebutkan tahapan utama proses data mining!
- Peran data mining
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- What are the steps in mining process?
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- Data mining roadmap