Zobrazeno 1 - 10
of 830
pro vyhledávání: '"H Stumpf"'
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-10 (2024)
Abstract Cells are the fundamental units of life, and like all life forms, they change over time. Changes in cell state are driven by molecular processes; of these many are initiated when molecule numbers reach and exceed specific thresholds, a chara
Externí odkaz:
https://doaj.org/article/a6d274e70b7c42eeb9bb212309241b86
Publikováno v:
Royal Society Open Science, Vol 11, Iss 7 (2024)
Single-cell technologies allow us to gain insights into cellular processes at unprecedented resolution. In stem cell and developmental biology snapshot data allow us to characterize how the transcriptional states of cells change between successive ce
Externí odkaz:
https://doaj.org/article/bee8b93b35bb42b799e18a0f87a5b101
Autor:
Christina L. Bloomfield, Joyce Gong, Steven Droho, Hadijat M. Makinde, Miranda G. Gurra, Cecilia H. Stumpf, Arjun Kharel, Gaurav Gadhvi, Deborah R. Winter, Weiguo Cui, Carla M. Cuda, Jeremy A. Lavine
Publikováno v:
Frontiers in Immunology, Vol 15 (2024)
IntroductionMacrophage function is determined by microenvironment and origin. Brain and retinal microglia are both derived from yolk sac progenitors, yet their microenvironments differ. Utilizing single-cell RNA sequencing (scRNA-seq) data from mice,
Externí odkaz:
https://doaj.org/article/45a0ccb3c3f748c78089ca3719ba45ea
Autor:
Irene Robles-Rebollo, Sergi Cuartero, Adria Canellas-Socias, Sarah Wells, Mohammad M. Karimi, Elisabetta Mereu, Alexandra G. Chivu, Holger Heyn, Chad Whilding, Dirk Dormann, Samuel Marguerat, Inmaculada Rioja, Rab K. Prinjha, Michael P. H. Stumpf, Amanda G. Fisher, Matthias Merkenschlager
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-16 (2022)
Here the authors show inducible genes and enhancers are regulated mainly by transcriptional burst frequency and that this is coordinated in single cells and individual alleles. Cohesin, which is important for inducible gene expression, is largely dis
Externí odkaz:
https://doaj.org/article/fc245dbd45344cc8acb6dc172ee905b9
Autor:
Léo P. M. Diaz, Michael P. H. Stumpf
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-9 (2022)
Abstract Network inference is a notoriously challenging problem. Inferred networks are associated with high uncertainty and likely riddled with false positive and false negative interactions. Especially for biological networks we do not have good way
Externí odkaz:
https://doaj.org/article/a50ac47da3f148998ce0ce31c274ad00
Autor:
Anissa Guillemin, Michael P. H. Stumpf
Publikováno v:
Mathematical Biosciences and Engineering, Vol 17, Iss 6, Pp 7916-7930 (2020)
Statistical physics provides a useful perspective for the analysis of many complex systems; it allows us to relate microscopic fluctuations to macroscopic observations. Developmental biology, but also cell biology more generally, are examples where a
Externí odkaz:
https://doaj.org/article/791354fe8b3947748b4302456f1db7ce
Autor:
Michael P H Stumpf, Carsten Wiuf
Networks provide a very useful way to describe a wide range of different data types in biology, physics and elsewhere. Apart from providing a convenient tool to visualize highly dependent data, networks allow stringent mathematical and statistical an
Publikováno v:
Royal Society Open Science, Vol 8, Iss 10 (2021)
In many scientific and technological contexts, we have only a poor understanding of the structure and details of appropriate mathematical models. We often, therefore, need to compare different models. With available data we can use formal statistical
Externí odkaz:
https://doaj.org/article/b98996487bc64752a237f3e347dc854a
Publikováno v:
BMC Bioinformatics, Vol 20, Iss 1, Pp 1-12 (2019)
Abstract Background Reverse engineering of gene regulatory networks from time series gene-expression data is a challenging problem, not only because of the vast sets of candidate interactions but also due to the stochastic nature of gene expression.
Externí odkaz:
https://doaj.org/article/1e3870531b6b48d79425fda5b781e48e
Publikováno v:
Nature Communications, Vol 9, Iss 1, Pp 1-9 (2018)
Signalling responses are marked by substantial cell-to-cell variability. Here, the authors propose an information theoretic framework that accounts for multiple inputs and temporal dynamics to analyse how signals flow through shared network component
Externí odkaz:
https://doaj.org/article/2daf3e307ce74d31936f4ab4d8af4613