CORE
CO
nnecting
RE
positories
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Research partnership
About
About
About us
Our mission
Team
Blog
FAQs
Contact us
Community governance
Governance
Advisory Board
Board of supporters
Research network
Innovations
Our research
Labs
research
Analysis of regulatory network involved in mechanical induction of embryonic stem cell differentiation
Authors
I Banerjee
M Jaramillo
+3 more
P Kumta
S Singh
X Zhang
Publication date
27 April 2012
Publisher
'Public Library of Science (PLoS)'
Doi
View
on
PubMed
Abstract
Embryonic stem cells are conventionally differentiated by modulating specific growth factors in the cell culture media. Recently the effect of cellular mechanical microenvironment in inducing phenotype specific differentiation has attracted considerable attention. We have shown the possibility of inducing endoderm differentiation by culturing the stem cells on fibrin substrates of specific stiffness [1]. Here, we analyze the regulatory network involved in such mechanically induced endoderm differentiation under two different experimental configurations of 2-dimensional and 3-dimensional culture, respectively. Mouse embryonic stem cells are differentiated on an array of substrates of varying mechanical properties and analyzed for relevant endoderm markers. The experimental data set is further analyzed for identification of co-regulated transcription factors across different substrate conditions using the technique of bi-clustering. Overlapped bi-clusters are identified following an optimization formulation, which is solved using an evolutionary algorithm. While typically such analysis is performed at the mean value of expression data across experimental repeats, the variability of stem cell systems reduces the confidence on such analysis of mean data. Bootstrapping technique is thus integrated with the bi-clustering algorithm to determine sets of robust bi-clusters, which is found to differ significantly from corresponding bi-clusters at the mean data value. Analysis of robust bi-clusters reveals an overall similar network interaction as has been reported for chemically induced endoderm or endodermal organs but with differences in patterning between 2-dimensional and 3-dimensional culture. Such analysis sheds light on the pathway of stem cell differentiation indicating the prospect of the two culture configurations for further maturation. © 2012 Zhang et al
Similar works
Full text
Open in the Core reader
Download PDF
Available Versions
Public Library of Science (PLOS)
See this paper in CORE
Go to the repository landing page
Download from data provider
Last time updated on 18/09/2018
Directory of Open Access Journals
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:doaj.org/article:19c670405...
Last time updated on 14/10/2017
Name not available
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:d-scholarship.pitt.edu:141...
Last time updated on 23/11/2016
D-Scholarship@Pitt
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:d-scholarship.pitt.edu:141...
Last time updated on 19/07/2013
Public Library of Science (PLOS)
See this paper in CORE
Go to the repository landing page
Download from data provider
Last time updated on 05/06/2019
Name not available
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:d-scholarship.pitt.edu:141...
Last time updated on 15/12/2016
Crossref
See this paper in CORE
Go to the repository landing page
Download from data provider
info:doi/10.1371%2Fjournal.pon...
Last time updated on 18/03/2019