 Markov Chains
"Markov Chains" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
A stochastic process such that the conditional probability distribution for a state at any future instant, given the present state, is unaffected by any additional knowledge of the past history of the system.
| Descriptor ID |
D008390
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| MeSH Number(s) |
E05.318.740.600.500 E05.318.740.996.500 G17.830.500 N05.715.360.750.625.500 N05.715.360.750.770.500 N06.850.520.830.600.500 N06.850.520.830.996.500
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| Concept/Terms |
Markov Chains- Markov Chains
- Chains, Markov
- Markov Process
- Markov Processes
- Process, Markov
- Processes, Markov
- Markov Chain
- Chain, Markov
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Below are MeSH descriptors whose meaning is more general than "Markov Chains".
Below are MeSH descriptors whose meaning is more specific than "Markov Chains".
This graph shows the total number of publications written about "Markov Chains" by people in this website by year, and whether "Markov Chains" was a major or minor topic of these publications.
To see the data from this visualization as text, click here.
| Year | Major Topic | Minor Topic | Total |
|---|
| 2009 | 0 | 2 | 2 | | 2010 | 0 | 1 | 1 | | 2012 | 1 | 1 | 2 | | 2016 | 1 | 0 | 1 | | 2018 | 1 | 1 | 2 |
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Below are the most recent publications written about "Markov Chains" by people in Profiles.
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Shokoohi F, Stephens DA, Bourque G, Pastinen T, Greenwood CMT, Labbe A. A hidden markov model for identifying differentially methylated sites in bisulfite sequencing data. Biometrics. 2019 03; 75(1):210-221.
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Ries D, Carriquiry A, Shook R. Modeling energy balance while correcting for measurement error via free knot splines. PLoS One. 2018; 13(8):e0201892.
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Benoit JS, Chan W, Luo S, Yeh HW, Doody R. A hidden Markov model approach to analyze longitudinal ternary outcomes when some observed states are possibly misclassified. Stat Med. 2016 Apr 30; 35(9):1549-57.
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Han B, Chen XW, Talebizadeh Z, Xu H. Genetic studies of complex human diseases: characterizing SNP-disease associations using Bayesian networks. BMC Syst Biol. 2012; 6 Suppl 3:S14.
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Yeh HW, Ellerbeck EF, Mahnken JD. Simultaneous evaluation of abstinence and relapse using a Markov chain model in smokers enrolled in a two-year randomized trial. BMC Med Res Methodol. 2012 Jul 07; 12:95.
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Fridley BL, Lund S, Jenkins GD, Wang L. A Bayesian integrative genomic model for pathway analysis of complex traits. Genet Epidemiol. 2012 May; 36(4):352-9.
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Han B, Chen XW, Talebizadeh Z. FEPI-MB: identifying SNPs-disease association using a Markov Blanket-based approach. BMC Bioinformatics. 2011 Nov 24; 12 Suppl 12:S3.
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Wagner JR, Ge B, Pokholok D, Gunderson KL, Pastinen T, Blanchette M. Computational analysis of whole-genome differential allelic expression data in human. PLoS Comput Biol. 2010 Jul 08; 6(7):e1000849.
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Bi C. A Monte Carlo EM algorithm for de novo motif discovery in biomolecular sequences. IEEE/ACM Trans Comput Biol Bioinform. 2009 Jul-Sep; 6(3):370-86.
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Goode EL, Fridley BL, Vierkant RA, Cunningham JM, Phelan CM, Anderson S, Rider DN, White KL, Pankratz VS, Song H, Hogdall E, Kjaer SK, Whittemore AS, DiCioccio R, Ramus SJ, Gayther SA, Schildkraut JM, Pharaoh PP, Sellers TA. Candidate gene analysis using imputed genotypes: cell cycle single-nucleotide polymorphisms and ovarian cancer risk. Cancer Epidemiol Biomarkers Prev. 2009 Mar; 18(3):935-44.
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