Zobrazeno 1 - 10
of 112
pro vyhledávání: '"Jack Kuipers"'
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-13 (2023)
Abstract Reconstructing the history of somatic DNA alterations can help understand the evolution of a tumor and predict its resistance to treatment. Single-cell DNA sequencing (scDNAseq) can be used to investigate clonal heterogeneity and to inform p
Externí odkaz:
https://doaj.org/article/5f81aed31c784eff80c00c66b4192dda
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-14 (2023)
Abstract Cancer progression is an evolutionary process shaped by both deterministic and stochastic forces. Multi-region and single-cell sequencing of tumors enable high-resolution reconstruction of the mutational history of each tumor and highlight t
Externí odkaz:
https://doaj.org/article/4690b2c5113f4450b93657b7b3827168
Publikováno v:
Journal of Statistical Software, Vol 105, Pp 1-31 (2023)
The R package BiDAG implements Markov chain Monte Carlo (MCMC) methods for structure learning and sampling of Bayesian networks. The package includes tools to search for a maximum a posteriori (MAP) graph and to sample graphs from the posterior distr
Externí odkaz:
https://doaj.org/article/6029218b32d0457a8897ec04aaa04bcc
Autor:
Senbai Kang, Nico Borgsmüller, Monica Valecha, Jack Kuipers, Joao M. Alves, Sonia Prado-López, Débora Chantada, Niko Beerenwinkel, David Posada, Ewa Szczurek
Publikováno v:
Genome Biology, Vol 23, Iss 1, Pp 1-33 (2022)
Abstract We present SIEVE, a statistical method for the joint inference of somatic variants and cell phylogeny under the finite-sites assumption from single-cell DNA sequencing. SIEVE leverages raw read counts for all nucleotides and corrects the acq
Externí odkaz:
https://doaj.org/article/effa6828cc9d44b49baa18e46c9ce1f7
Autor:
Polina Suter, Eva Dazert, Jack Kuipers, Charlotte K Y Ng, Tuyana Boldanova, Michael N Hall, Markus H Heim, Niko Beerenwinkel
Publikováno v:
PLoS Computational Biology, Vol 18, Iss 9, p e1009767 (2022)
Comprehensive molecular characterization of cancer subtypes is essential for predicting clinical outcomes and searching for personalized treatments. We present bnClustOmics, a statistical model and computational tool for multi-omics unsupervised clus
Externí odkaz:
https://doaj.org/article/00fabc0f584743428d737f10c282a558
Autor:
Anne Bertolini, Michael Prummer, Mustafa Anil Tuncel, Ulrike Menzel, María Lourdes Rosano-González, Jack Kuipers, Daniel Johannes Stekhoven, Tumor Profiler consortium, Niko Beerenwinkel, Franziska Singer
Publikováno v:
PLoS Computational Biology, Vol 18, Iss 6, p e1010097 (2022)
Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful technique to decipher tissue composition at the single-cell level and to inform on disease mechanisms, tumor heterogeneity, and the state of the immune microenvironment. Although multip
Externí odkaz:
https://doaj.org/article/07bd54c0cd3f489b8de251a12bee74b2
Autor:
Kiyomi Morita, Feng Wang, Katharina Jahn, Tianyuan Hu, Tomoyuki Tanaka, Yuya Sasaki, Jack Kuipers, Sanam Loghavi, Sa A. Wang, Yuanqing Yan, Ken Furudate, Jairo Matthews, Latasha Little, Curtis Gumbs, Jianhua Zhang, Xingzhi Song, Erika Thompson, Keyur P. Patel, Carlos E. Bueso-Ramos, Courtney D. DiNardo, Farhad Ravandi, Elias Jabbour, Michael Andreeff, Jorge Cortes, Kapil Bhalla, Guillermo Garcia-Manero, Hagop Kantarjian, Marina Konopleva, Daisuke Nakada, Nicholas Navin, Niko Beerenwinkel, P. Andrew Futreal, Koichi Takahashi
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-17 (2020)
Understanding the evolutionary trajectory of cancer samples may enable understanding resistance to treatment. Here, the authors used single cell sequencing of a cohort of acute myeloid leukemia tumours and identify features of linear and branching ev
Externí odkaz:
https://doaj.org/article/c334158e79f74f09bd8df84c3b7562c1
Autor:
Jack Kuipers, Ariane L Moore, Katharina Jahn, Peter Schraml, Feng Wang, Kiyomi Morita, P Andrew Futreal, Koichi Takahashi, Christian Beisel, Holger Moch, Niko Beerenwinkel
Publikováno v:
PLoS Computational Biology, Vol 17, Iss 12, p e1009036 (2021)
Tumour progression is an evolutionary process in which different clones evolve over time, leading to intra-tumour heterogeneity. Interactions between clones can affect tumour evolution and hence disease progression and treatment outcome. Intra-tumour
Externí odkaz:
https://doaj.org/article/e99cbb4fb35d4870a878164193d88cb4
Autor:
Susana Posada-Céspedes, Gert Van Zyl, Hesam Montazeri, Jack Kuipers, Soo-Yon Rhee, Roger Kouyos, Huldrych F Günthard, Niko Beerenwinkel
Publikováno v:
PLoS Computational Biology, Vol 17, Iss 9, p e1008363 (2021)
Although combination antiretroviral therapies seem to be effective at controlling HIV-1 infections regardless of the viral subtype, there is increasing evidence for subtype-specific drug resistance mutations. The order and rates at which resistance m
Externí odkaz:
https://doaj.org/article/234cad3e39d142a49b86b6057a9e52e3
Publikováno v:
Nature Communications, Vol 10, Iss 1, Pp 1-12 (2019)
Intra-tumour heterogeneity provides important information about subclonal tumour evolution. Here, the authors develop B-SCITE, a computational method for inferring tumour phylogenies from combined single-cell and bulk sequencing data.
Externí odkaz:
https://doaj.org/article/ef258a1885df4088abb09ed93505c2e3