Hobolth A - Search Results

1

A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data.

Bertl J, Guo Q, Juul M, Besenbacher S, Nielsen MM, Hornshøj H, Pedersen JS, Hobolth A. Bertl J, et al. Among authors: hobolth a. BMC Bioinformatics. 2018 Apr 19;19(1):147. doi: 10.1186/s12859-018-2141-2. BMC Bioinformatics. 2018. PMID: 29673314 Free PMC article.

2

Comparative analysis of protein coding sequences from human, mouse and the domesticated pig.

Jørgensen FG, Hobolth A, Hornshøj H, Bendixen C, Fredholm M, Schierup MH. Jørgensen FG, et al. Among authors: hobolth a. BMC Biol. 2005 Jan 28;3:2. doi: 10.1186/1741-7007-3-2. BMC Biol. 2005. PMID: 15679890 Free PMC article.

3

Comparison of methods for calculating conditional expectations of sufficient statistics for continuous time Markov chains.

Tataru P, Hobolth A. Tataru P, et al. Among authors: hobolth a. BMC Bioinformatics. 2011 Dec 5;12:465. doi: 10.1186/1471-2105-12-465. BMC Bioinformatics. 2011. PMID: 22142146 Free PMC article.

4

The multivariate Wright-Fisher process with mutation: Moment-based analysis and inference using a hierarchical Beta model.

Hobolth A, Siren J. Hobolth A, et al. Theor Popul Biol. 2016 Apr;108:36-50. doi: 10.1016/j.tpb.2015.11.001. Epub 2015 Nov 29. Theor Popul Biol. 2016. PMID: 26612605

5

An alternative derivation of the stationary distribution of the multivariate neutral Wright-Fisher model for low mutation rates with a view to mutation rate estimation from site frequency data.

Schrempf D, Hobolth A. Schrempf D, et al. Among authors: hobolth a. Theor Popul Biol. 2017 Apr;114:88-94. doi: 10.1016/j.tpb.2016.12.001. Epub 2016 Dec 29. Theor Popul Biol. 2017. PMID: 28041892 Free article.

6

Statistical Inference in the Wright-Fisher Model Using Allele Frequency Data.

Tataru P, Simonsen M, Bataillon T, Hobolth A. Tataru P, et al. Among authors: hobolth a. Syst Biol. 2017 Jan 1;66(1):e30-e46. doi: 10.1093/sysbio/syw056. Syst Biol. 2017. PMID: 28173553 Free PMC article. Review.

7

Significance evaluation in factor graphs.

Madsen T, Hobolth A, Jensen JL, Pedersen JS. Madsen T, et al. Among authors: hobolth a. BMC Bioinformatics. 2017 Mar 31;18(1):199. doi: 10.1186/s12859-017-1614-z. BMC Bioinformatics. 2017. PMID: 28359297 Free PMC article.

8

Non-coding cancer driver candidates identified with a sample- and position-specific model of the somatic mutation rate.

Juul M, Bertl J, Guo Q, Nielsen MM, Świtnicki M, Hornshøj H, Madsen T, Hobolth A, Pedersen JS. Juul M, et al. Among authors: hobolth a. Elife. 2017 Mar 31;6:e21778. doi: 10.7554/eLife.21778. Elife. 2017. PMID: 28362259 Free PMC article.

9

Pan-cancer screen for mutations in non-coding elements with conservation and cancer specificity reveals correlations with expression and survival.

Hornshøj H, Nielsen MM, Sinnott-Armstrong NA, Świtnicki MP, Juul M, Madsen T, Sallari R, Kellis M, Ørntoft T, Hobolth A, Pedersen JS. Hornshøj H, et al. Among authors: hobolth a. NPJ Genom Med. 2018 Jan 11;3:1. doi: 10.1038/s41525-017-0040-5. eCollection 2018. NPJ Genom Med. 2018. PMID: 29354286 Free PMC article.

10

ncdDetect2: improved models of the site-specific mutation rate in cancer and driver detection with robust significance evaluation.

Juul M, Madsen T, Guo Q, Bertl J, Hobolth A, Kellis M, Pedersen JS. Juul M, et al. Among authors: hobolth a. Bioinformatics. 2019 Jan 15;35(2):189-199. doi: 10.1093/bioinformatics/bty511. Bioinformatics. 2019. PMID: 29945188 Free PMC article.

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