Results 81 to 90 of about 2,557,835 (263)

Detecting microRNA activity from gene expression data

open access: yesBMC Bioinformatics, 2010
Background MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation.
Fitzgerald Katherine A   +6 more
doaj   +1 more source

Septin 9 PB domains coordinate centrosome positioning and microtubule acetylation to control epithelial polarity

open access: yesFEBS Letters, EarlyView.
Septin 9 polybasic domains couple phosphoinositide‐rich membrane binding to centrosome positioning, Golgi organization, and microtubule acetylation to control epithelial polarity. Their loss disrupts this axis, causing centrosome mispositioning, Golgi fragmentation, reduced microtubule acetylation, and polarity inversion via upregulation of the ...
Ting ting Cai   +4 more
wiley   +1 more source

Integrating Gene Expression Data Into Genomic Prediction

open access: yesFrontiers in Genetics, 2019
Gene expression profiles potentially hold valuable information for the prediction of breeding values and phenotypes. In this study, the utility of transcriptome data for phenotype prediction was tested with 185 inbred lines of Drosophila melanogaster for
Zhengcao Li   +3 more
doaj   +1 more source

Rab14 regulates the transport of human papillomavirus to the trans‐Golgi network for infectious cell entry

open access: yesFEBS Letters, EarlyView.
This study reveals that the small GTPase Rab14 is necessary for human papillomavirus (HPV) infection and plays an essential role in the transport of virions to the trans‐Golgi network (TGN). HPV in the early endosome (EE), which harbors GTP‐bound Rab14, is transported to the TGN through the switch of Rab14 from its GTP‐bound to GDP‐bound form.
Yoshiyuki Ishii, Iwao Kukimoto
wiley   +1 more source

Inference of gene networks using gene expression data with applications

open access: yesHeliyon
Gene networks (GNs) use graphs to represent the interaction relationships between genes. Large-scale GNs are often sparse and contain hub genes that interact with many other genes.
Chi-Kan Chen
doaj   +1 more source

Modulation of Homer1 EVH1 domain internal dynamics by putative autism‐associated mutations

open access: yesFEBS Letters, EarlyView.
The putative autism‐associated M65I and S97L variants of the EVH1 domain of the postsynaptic scaffold protein Homer1 do not exhibit substantial changes in their overall structure or partner binding. Both of them, but especially the M65I variant, show altered internal dynamics relative to the wild‐type domain on the μs‐ms timescale, indicated by the ...
Fanni Farkas   +6 more
wiley   +1 more source

Visualisation and analysis of gene expression data [PDF]

open access: yesNature Genetics, 1999
P roducing microarray data starts with scanning in the glass, gel or plastic slides with a specialized scanner to obtain digital images of the results of an experiment after hybridization. With the help of image analysis software the DNA expression levels are then quantified.
openaire   +1 more source

SCANPY: large-scale single-cell gene expression data analysis

open access: yesGenome Biology, 2018
Scanpy is a scalable toolkit for analyzing single-cell gene expression data. It includes methods for preprocessing, visualization, clustering, pseudotime and trajectory inference, differential expression testing, and simulation of gene regulatory ...
F. Alexander Wolf   +2 more
doaj   +1 more source

An unexpected alternative viologen electron mediator site in tungsten‐containing formate dehydrogenase

open access: yesFEBS Letters, EarlyView.
An unexpected alternative interaction site for ethyl viologen was identified in formate dehydrogenase 1 from Methylorubrum extorquens. Combined mutagenesis, kinetic analysis, and docking revealed that aromatic residues near an iron–sulfur cluster enable flavin mononucleotide‐independent electron transfer, offering a framework for engineering improved ...
Eleni G. Poloniataki, Yong Hwan Kim
wiley   +1 more source

Cell geometry and membrane protein crowding constrain Escherichia coli growth rate, overflow metabolism, respiration, and maintenance energy

open access: yesFEBS Letters, EarlyView.
The physical dimensions and shape of bacterial cells define the surface area available to acquire nutrients and the volume available for synthesizing proteins and DNA. Here, we use computational systems biology to decode the importance of cell geometry as a major determinant of prokaryotic phenotype, including growth rate and metabolic efficiency. This
Ross P. Carlson   +6 more
wiley   +1 more source

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