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SAMPLES (424)
mace:id
Technology # Array version
# SEVERAL # # SEVERAL
Affymetrix # HGU 133 Plus 2
Affymetrix # MGU 74 Av2
Affymetrix # MoGene V1.0st
Affymetrix # Mouse 430A
Affymetrix # Rhesus
Agilent # AGHUMAN
Agilent # AGMOUSE
Applied Biosystems # HGS V1
Applied Biosystems # HGS V2
Applied Biosystems # MGS V1
Applied Biosystems # MGS V2
Applied Biosystems # RGS V1
Genopole SXB # SXBH1
Genopole SXB # SXBH2
Genopole SXB # SXBH3
Genopole SXB # SXBM1
Genopole SXB # SXBM2
Genopole SXB # SXBM3
Illumina # HumanHT-12 V4.0
Illumina # HUMANWG6v3
Illumina # MouseWG-6 v2.0
Species
# SEVERAL
Cercocebus atys
Chlorocebus sabaeus
Homo sapiens
Macaca mulatta
Macaca Nemestrina
Mus musculus
Pan troglodytes
Rattus norvegicus
Organ
# OTHER
# SEVERAL
Adenoid
Adrenal gland
Bladder
Blood
Blood vessel
Brain
Bronchi
Cervix
Embryo
Esophagus
Gallblader
Heart
Hypotalamus
Intestine
Kidney
Larynx
Liver
Lung
Lymph node
Mammary gland
Mussle
Pancreas
Parathyroid
Penis
Pharynx
Pineal gland
Pituitary gland
Prostate
Salivary gland
Seminal vesicle
Skin
Spinal cord
Spleen
Stomach
Test
Thymus
Thyroid
Tonsil
Trachea
Ureter
Uterus
Vagina
Vas deferens
Tissue
# OTHER
# SEVERAL
Bone Marrow
Connective - Dense Irregular Tissue (Collagen)
Connective - Dense Regular Tissue (Collagen)
Connective - Dense Regular Tissue (Elastic)
Connective - Loose Tissue (Adipose)
Connective - Loose Tissue (Areolar)
Connective - Loose Tissue (Reticular)
Epithelium - Simple (Columnar)
Epithelium - Simple (Cuboidal)
Epithelium - Simple (Pseudostratified)
Epithelium - Simple (Squamous)
Epithelium - Stratified (Columnar / Cuboidal)
Epithelium - Stratified (Squamous: Keratinized)
Epithelium - Stratified (Squamous: NonKeratinized)
Fluid - Blood
Fluid - Lymph
Gland - Endocrine Glands
Gland - Exocrine Glands (Ducts and Tubules)
Muscle - Non-striated
Muscle - Striated (Cardiac)
Muscle - Striated (Skeletal)
Nervous - Nerves
Nervous - Neurons (Bipolar)
Nervous - Neurons (Multipolar)
Nervous - Neurons (Unipolar)
Nervous - Receptors
Placenta
Stem cells
Supportive - Cartilage (Elastic)
Supportive - Cartilage (Fibrocartilage)
Supportive - Cartilage (Hyaline)
Supportive - Osseous (Compact)
Supportive - Osseous (Spongey)
Physiopathology
# HEALTHY
# OTHER
# SEVERAL
apoptosis
autocrine signaling
differentiation
drug response
electric response
endocrine signaling
environemental response
homeostasis
immune response
mechanic response
necrosis
paracrine signaling
proliferation
Type
# OTHER
# SEVERAL
conditional knockout
drug stress
electric stress
environmental stress
ground state
immune stress
knockdown RNAi
knockout
mechanic stress
stable transfection
time course
transient transfection
Name
Attached file
download project data file ('.map')
Attached file (see:
ruid website
)
download project data file ('.map' RUID converted)
Attached file
download raw data files ('.zip')
Attached file
download annotation files ('.zip')
User name
Nicolas Tchitchek
Email
nicolas.tchitchek@ihes.fr
Phone / Fax number
0033610887604 /
Location
Institut des Hautes Études Scientifiques (Systems Epigenomics Group) - 35, route de Chartres - 91440 Bures-sur-Yvette, FRANCE
Scientific description
From abstract of the published article: Gene regulatory networks inferred from RNA abundance data have generated significant interest, but despite this, gene network approaches are used infrequently and often require input from bioinformaticians. We have assembled a suite of tools for analysing regulatory networks, and we illustrate their use with microarray datasets generated in human endothelial cells. We infer a range of regulatory networks, and based on this analysis discuss the strengths and limitations of network inference from RNA abundance data. We welcome contact from researchers interested in using our inference and visualization tools to answer biological questions.
Technical description
From materials and methods section of the published article: Cell culture, siRNA transfection and tumour necrosis factor treatment: Umbilical cords were collected after written informed consent was given and approval of the study received from the Cambridge Research Ethics Committee. Human umbilical vein endothelial cells (HUVECs) were isolated from umbilical cords by collagenase digestion and cultured at 37°C/5% CO2 in basal culture medium supplemented with a proprietary mixture of heparin, hydrocortisone, epidermal growth factor, fibroblast growth factor, 2% fetal calf serum (FCS) (EGM-2, Cambrex, Workingham, UK). Equal numbers of HUVECs from 10 individuals were pooled, plated at 2.5 × 105 cells/well in six-well plates and allowed to recover for 24 h, at which time they were ∼70% confluent. To support the choice of pooling 10 biological isolates to minimize individual variation in our dataset, we carried out an in silico pooling experiment. Using microarray expression data from 15 different HUVEC isolates, we assessed how individual variance in the dataset decreased when the mean expression value for an increasing number of isolates was calculated. Mean expression values were calculated for all combinations of the 15 different HUVEC isolates on a gene by gene basis. The variance between all combinations of the mean values was then calculated and the ratios between all variance values above an arbitrarily set minimum threshold value calculated for all combinations of the mean. The mean value of the variance ratios for each ‘meaned’ group of isolates was then plotted against the mean number of isolates (Supplementary File S1). It can be seen from the curve that even when a more stringent variance threshold of 1.5 is used, increasing the number of isolates pooled beyond 10 individuals will not result in an additional marked decrease in the individual variability in the dataset. Four hundred transcription factors, signalling molecules, receptors and ligands were selected as siRNA targets based on their relevance to endothelial biology and pathology. siRNA ‘smartpools’ from Dharmacon Inc. (Lafayette, CO, USA) were transfected into the cells using the siFectamine transfection reagent (ICVEC, London, UK) used according to the manufacturer's instructions. To generate a time course dataset related to inflammatory conditions, pools of 70% confluent HUVECs isolated and cultured as above were treated for 24 h with 10 ng/ml tumour necrosis factor (TNF-α). RNA preparation and gene array analysis: Total RNA was prepared using Trizol reagent (Invitrogen, London, UK) and assessed using an Agilent 2100 bioanalyser. Biotin-labelled complex cRNAs were prepared and hybridized to CodeLink UniSet Human 20K Bioarray microarrays according to the manufacturer's protocols (GE Healthcare, Amersham, UK). The quality of the expression data from all chips was confirmed using CodeLink Expression Analysis Software (version 4.1). To ensure that expression levels were comparable between the arrays the data was normalized using the cyclic Loess method (42).
Reference
Hurley D, Araki H, Tamada Y, Dunmore B et al. Gene network inference and visualization tools for biologists: application to new human transcriptome datasets. Nucleic Acids Res 2012 Mar 1;40(6):2377-2398. PMID: 22121215
Pubmed : http://www.ncbi.nlm.nih.gov/pubmed/22121215