A dynamic programming algorithm for haplotype block partitioning
By Kui Zhang, Minghua Deng, Ting Chen, Michael S. Waterman, Fengzhu Sun. Proceedings of the National Academy of Sciences of the United States of America, 2002
366 citations recorded by the source corpus.
Subfields: Genetics, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/124059ccfac991e1c7cdd9b45ae82582ca17acc4
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In Genetics
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In Molecular Biology
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Citations in the corpus
- The linkage disequilibrium and the selection of genetic markers for association studies in European populations (2007, methodology): “developed a dynamic programming algorithm for haplotype block partitioning as an optimal solution to the problem (Zhang et al. 2002).”
- Robust inference with knockoffs (2018, methodology): “Returning to our genetic example, it has been shown that the joint distribution of SNPs may be accurately modeled by hidden Markov models (see [14, 16, 12, 10] for some early formulations), and there certainly is an abundance of genotype data to estimate the various model parameters; compare for ins”
- Selecting additional tag SNPs for tolerating missing data in genotyping (2005, neutral): “Proof. When m = 0, MRTS is the same as the original problem of finding minimum tag SNPs, which is known as the minimum test set problem [6, 17 ].”
- Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium. (2004, methodology): “…early publications on this topic focused on simply resolving common haplotypes (Johnson et al. 2001), and more quantitative methods have been described that minimize the number of tagSNPs required for this task (Zhang et al. 2002b; Ackerman et al. 2003; Ke and Cardon 2003; Meng et al. 2003).”
- Haplotype blocks and linkage disequilibrium in the human genome (2003, methodology): “These studies either used PRE-ASCERTAINED SNPS from public data- bases 32,46,48 , which limited the resolution to a mean marker spacing of ~5–20 kb or, in the case of Patil et al. 45 , used chip-based resequencing on a relatively small sample of 20 chromosomes.”