Results 81 to 90 of about 8,545,689 (298)

A systems biology approach to construct the gene regulatory network of systemic inflammation via microarray and databases mining

BMC Medical Genomics, 2008
Background Inflammation is a hallmark of many human diseases. Elucidating the mechanisms underlying systemic inflammation has long been an important topic in basic and clinical research. When primary pathogenetic events remains unclear due to its immense
Lan Chung-Yu, Yang Shih-Kuang, Chen Bor-Sen, Chuang Yung-Jen   +3 more
doaj   +1 more source

The inferred cardiogenic gene regulatory network in the mammalian heart. [PDF]

PLoS ONE, 2014
Cardiac development is a complex, multiscale process encompassing cell fate adoption, differentiation and morphogenesis. To elucidate pathways underlying this process, a recently developed algorithm to reverse engineer gene regulatory networks was ...
Jason N Bazil, Karl D Stamm, Xing Li, Raghuram Thiagarajan, Timothy J Nelson, Aoy Tomita-Mitchell, Daniel A Beard   +6 more
doaj   +1 more source

Ligand‐dependent transcriptional heterogeneity in cell cycle gene expression delays G1/S entry

FEBS Letters, EarlyView.
EGF and HRG induce distinct G1/S progression programs in ErbB2‐amplified BT474 breast cancer cells. Despite activating the potent ErbB2–ErbB3 heterodimer, HRG does not accelerate cell‐cycle entry. Instead, EGF promotes earlier restriction‐point passage via ERK–FOS signaling, whereas HRG activates the AKT–MYC axis, driving transcriptional heterogeneity ...
Ririn Rahmala Febri, Ayaka Nagasato‐Ichikawa, Keita Iida, Shuhei Kimura, Akira Imamoto, Mariko Okada   +5 more
wiley   +1 more source

Estimating gene regulatory networks with pandaR [PDF]

Bioinformatics, 2017
Abstract PANDA (Passing Attributes between Networks for Data Assimilation) is a gene regulatory network inference method that begins with a model of transcription factor–target gene interactions and uses message passing to update the network model given available transcriptomic and protein–protein interaction data.
Daniel Schlauch, Joseph N. Paulson, Albert Young, Kimberly Glass, John Quackenbush   +4 more
openaire   +5 more sources

Translophagy—A potential link between autophagy impairment and translational errors

FEBS Letters, EarlyView.
Neurodegenerative diseases are characterised by the accumulation of abnormal proteins and protein aggregates, but their origin often remains unknown. We propose that selective autophagy removes damaged protein‐making machinery, preventing errors during protein synthesis.
Mykola V. Korolchuk, Gailing Ma, Robin Antrobus, Diego Manni, Marco Trevisan‐Herraz, Mustafa Khwaja, Max Brown, Gavin D. Richardson, Masaaki Komatsu, Daniel Erskine, Viktor I. Korolchuk, Tetsushi Kataura   +11 more
wiley   +1 more source

Linking Cytoscape and the corynebacterial reference database CoryneRegNet [PDF]

, 2008
Baumbach J, Apeltsin L. Linking Cytoscape and the corynebacterial reference database CoryneRegNet. BMC Genomics. 2008;9(1): 184.Background: Recently, the research community has seen an influx of data relating to transcriptional regulatory interactions of
Baumbach Jan, Jan Baumbach, Apeltsin, Leonard, Baumbach, Jan, Apeltsin Leonard, Leonard Apeltsin   +5 more
core   +1 more source

Structures of mycobacterial 3‐methylcrotonyl‐CoA carboxylase reveal carrier‐domain translocation between catalytic sites

FEBS Letters, EarlyView.
Mycobacterial 3‐methylcrotonyl‐CoA carboxylase uses a mobile biotin‐carrying domain to shuttle a carboxyl group between two catalytic sites, enabling carboxylation of 3‐methylcrotonyl‐CoA during leucine breakdown. Cryo‐electron microscopy captures the carrier at both sites and reveals an inward loop movement that may prevent futile rebinding to the ...
Ajit Yadav, Bogdan I. Florea, Sebastian Geibel   +2 more
wiley   +1 more source

Fused Regression for Multi-source Gene Regulatory Network Inference.

PLoS Computational Biology, 2016
Understanding gene regulatory networks is critical to understanding cellular differentiation and response to external stimuli. Methods for global network inference have been developed and applied to a variety of species.
Kari Y Lam, Zachary M Westrick, Christian L Müller, Lionel Christiaen, Richard Bonneau   +4 more
doaj   +1 more source

From junk to function — How weak selection in eukaryotes builds new parts and drives genomic complexity

FEBS Letters, EarlyView.
How do genomes gain new functional parts? In eukaryotes, which tend to evolve under weak selection, much of the genome is junk. Palazzo and Qiu borrow the logic of Markov chains to show how non‐functional DNA becomes functional through the appearance of intermediate states, which arise due to epistasis, buffering, and biochemical messiness, allowing ...
Alexander F. Palazzo, Yi Qiu
wiley   +1 more source

hlh-1 and the C. elegans Body Wall Muscle Transcriptional Differentiation Network [PDF]

, 2011
To understand the structure and function of gene regulatory networks, it is important to first catalogue the components. Measurable constituents of networks include cis-regulatory elements, identified by their conservation and ability to drive expression;
Kuntz, Steven Gregory
core   +1 more source