BMC Systems Biology

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BTNET : boosted tree based gene regulatory network inference algorithm using time-course measurement data
BMC Systems Biology - Tập 12 - Trang 69-77 - 2018
Sungjoon Park, Jung Min Kim, Wonho Shin, Sung Won Han, Minji Jeon, Hyun Jin Jang, Ik-Soon Jang, Jaewoo Kang
Identifying gene regulatory networks is an important task for understanding biological systems. Time-course measurement data became a valuable resource for inferring gene regulatory networks. Various methods have been presented for reconstructing the networks from time-course measurement data. However, existing methods have been validated on only a limited number of benchmark datasets, and rarely ...... hiện toàn bộ
Erratum to: ppiPre: predicting protein-protein interactions by combining heterogeneous features
BMC Systems Biology - Tập 9 - Trang 1-1 - 2015
Yue Deng, Lin Gao, Bingbo Wang
ECOLITASTER: cellular biosensor
BMC Systems Biology - Tập 1 - Trang 1-2 - 2007
Guillermo Rodrigo, Javier Carreral, Alfonso Jaramillo
Network topology-based detection of differential gene regulation and regulatory switches in cell metabolism and signaling
BMC Systems Biology - Tập 8 - Trang 1-10 - 2014
Rosario M Piro, Stefan Wiesberg, Gunnar Schramm, Nico Rebel, Marcus Oswald, Roland Eils, Gerhard Reinelt, Rainer König
Common approaches to pathway analysis treat pathways merely as lists of genes disregarding their topological structures, that is, ignoring the genes' interactions on which a pathway's cellular function depends. In contrast, PathWave has been developed for the analysis of high-throughput gene expression data that explicitly takes the topology of networks into account to identify both global dysregu...... hiện toàn bộ
BacGrid: simulations of bacteria using the grid
BMC Systems Biology - Tập 1 - Trang 1-3 - 2007
Michael Lees, Brian Logan, John King
From correlation to causation networks: a simple approximate learning algorithm and its application to high-dimensional plant gene expression data
BMC Systems Biology - Tập 1 - Trang 1-10 - 2007
Rainer Opgen-Rhein, Korbinian Strimmer
The use of correlation networks is widespread in the analysis of gene expression and proteomics data, even though it is known that correlations not only confound direct and indirect associations but also provide no means to distinguish between cause and effect. For "causal" analysis typically the inference of a directed graphical model is required. However, this is rather difficult due to the curs...... hiện toàn bộ
Network component analysis provides quantitative insights on an Arabidopsis transcription factor-gene regulatory network
BMC Systems Biology - Tập 7 - Trang 1-13 - 2013
Ashish Misra, Ganesh Sriram
Gene regulatory networks (GRNs) are models of molecule-gene interactions instrumental in the coordination of gene expression. Transcription factor (TF)-GRNs are an important subset of GRNs that characterize gene expression as the effect of TFs acting on their target genes. Although such networks can qualitatively summarize TF-gene interactions, it is highly desirable to quantitatively determine th...... hiện toàn bộ
A system for success: BMC Systems Biology, a new open access journal
BMC Systems Biology - Tập 1 - Trang 1-3 - 2007
Matt J Hodgkinson, Penelope A Webb
BMC Systems Biology is the first open access journal spanning the growing field of systems biology from molecules up to ecosystems. The journal has launched as more and more institutes are founded that are similarly dedicated to this new approach. BMC Systems Biology builds on the ongoing success of the BMC series, providing a venue for all sound research in the systems-level analysis of biology.
Detecting microRNAs of high influence on protein functional interaction networks: a prostate cancer case study
BMC Systems Biology - Tập 6 Số 1 - Trang 112 - 2012
Mohammed Alshalalfa, Gary D. Bader, Anna Goldenberg, Quaid Morris, Reda Alhajj
Emergence of bimodal cell population responses from the interplay between analog single-cell signaling and protein expression noise
BMC Systems Biology - Tập 6 - Trang 1-12 - 2012
Marc R Birtwistle, Jens Rauch, Anatoly Kiyatkin, Edita Aksamitiene, Maciej Dobrzyński, Jan B Hoek, Walter Kolch, Babatunde A Ogunnaike, Boris N Kholodenko
Cell-to-cell variability in protein expression can be large, and its propagation through signaling networks affects biological outcomes. Here, we apply deterministic and probabilistic models and biochemical measurements to study how network topologies and cell-to-cell protein abundance variations interact to shape signaling responses. We observe bimodal distributions of extracellular signal-regula...... hiện toàn bộ
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