Advertisement

Topics

PubMed Journals Articles About "Corbus Pharmaceuticals Present Gene Expression Data From Recent" RSS

21:04 EST 15th January 2019 | BioPortfolio

Corbus Pharmaceuticals Present Gene Expression Data From Recent PubMed articles on BioPortfolio. Our PubMed references draw on over 21 million records from the medical literature. Here you can see the latest Corbus Pharmaceuticals Present Gene Expression Data From Recent articles that have been published worldwide.

More Information about "Corbus Pharmaceuticals Present Gene Expression Data From Recent" on BioPortfolio

We have published hundreds of Corbus Pharmaceuticals Present Gene Expression Data From Recent news stories on BioPortfolio along with dozens of Corbus Pharmaceuticals Present Gene Expression Data From Recent Clinical Trials and PubMed Articles about Corbus Pharmaceuticals Present Gene Expression Data From Recent for you to read. In addition to the medical data, news and clinical trials, BioPortfolio also has a large collection of Corbus Pharmaceuticals Present Gene Expression Data From Recent Companies in our database. You can also find out about relevant Corbus Pharmaceuticals Present Gene Expression Data From Recent Drugs and Medications on this site too.

Showing "Corbus Pharmaceuticals Present Gene Expression Data from Recent" PubMed Articles 1–25 of 63,000+

Gene networks and the evolution of plant morphology.

Elaboration of morphology depends on the precise orchestration of gene expression by key regulatory genes. The hierarchy and relationship among the participating genes is commonly known as gene regulatory network (GRN). Therefore, the evolution of morphology ultimately occurs by the rewiring of gene network structures or by the co-option of gene networks to novel domains. The availability of high-resolution expression data combined with powerful statistical tools have opened up new avenues to formulate and ...


Genetic Neural Networks: An artificial neural network architecture for capturing gene expression relationships.

Gene expression prediction is one of the grand challenges in computational biology. The availability of transcriptomics data combined with recent advances in artificial neural networks provide an unprecedented opportunity to create predictive models of gene expression with far reaching applications.

Clust: automatic extraction of optimal co-expressed gene clusters from gene expression data.

Identifying co-expressed gene clusters can provide evidence for genetic or physical interactions. Thus, co-expression clustering is a routine step in large-scale analyses of gene expression data. We show that commonly used clustering methods produce results that substantially disagree and that do not match the biological expectations of co-expressed gene clusters. We present clust, a method that solves these problems by extracting clusters matching the biological expectations of co-expressed genes and outpe...


BrainEXP: a database featuring with spatiotemporal expression variations and co-expression organizations in human brains.

Gene expression changes over the lifespan and varies among different tissues or cell types. Gene co-expression also changes by sex, age, different tissues or cell types. However, gene expression under the normal state and gene co-expression in the human brain has not been fully defined and quantified. Here we present a database named Brain EXPression Database (BrainEXP) which provides spatiotemporal expression of individual genes and co-expression in normal human brains. BrainEXP consists of 4,567 samples f...

Testing the gene expression classification of the EMT spectrum.

The epithelial-mesenchymal transition (EMT) plays a central role in cancer metastasis and drug resistance - two persistent clinical challenges. Epithelial cells can undergo a partial or full EMT, attaining either a hybrid epithelial/mesenchymal (E/M) or mesenchymal phenotype, respectively. Recent studies have emphasized that hybrid E/M cells may be more aggressive than their mesenchymal counterparts. However, mechanisms driving hybrid E/M phenotypes remain largely elusive. Here, to better characterize the h...

Loss of gene body methylation in Eutrema salsugineum is associated with reduced gene expression.

Gene body methylation (gbM) is typically characterized by DNA methylation in the CG context within coding regions, and is associated with constitutive genes that have moderate to high expression levels. A recent study discovered the loss of gbM in two plant species (Eutrema salsugineum and Conringia planisiliqua), illustrating that gbM is not necessary for survival and reproduction. The same paper stated there was no detectable effect of gbM loss on gene expression (GE). Here, we reanalyzed the GE data and ...

WEADE: A workflow for enrichment analysis and data exploration.

Data analysis based on enrichment of Gene Ontology terms has become an important step in exploring large gene or protein expression datasets and several stand-alone or web tools exist for that purpose. However, a comprehensive and consistent analysis downstream of the enrichment calculation is missing so far. With WEADE we present a free web application that offers an integrated workflow for the exploration of genomic data combining enrichment analysis with a versatile set of tools to directly compare and i...

Haemopedia RNA-seq: a database of gene expression during haematopoiesis in mice and humans.

During haematopoiesis, haematopoietic stem cells differentiate into restricted potential progenitors before maturing into the many lineages required for oxygen transport, wound healing and immune response. We have updated Haemopedia, a database of gene-expression profiles from a broad spectrum of haematopoietic cells, to include RNA-seq gene-expression data from both mice and humans. The Haemopedia RNA-seq data set covers a wide range of lineages and progenitors, with 57 mouse blood cell types (flow sorted ...

Novel symmetry-based gene-gene dissimilarity measures utilizing Gene Ontology: Application in gene clustering.

In recent years DNA microarray technology, leading to the generation of high-volume biological data, has gained significant attention. To analyze this high volume gene-expression data, one such powerful tool is Clustering. For any clustering algorithm, its efficiency majorly depends upon the underlying similarity/dissimilarity measure. During the analysis of such data often there is the need to further explore the similarity of genes not only with respect to their expression values but also with respect to ...

Gene expression cancer classification using modified K-Nearest Neighbors technique.

Gene expression microarray classification is a crucial research field as it has been employed in cancer prediction and diagnosis systems. Gene expression data are composed of dozens of samples characterized by thousands of genes. Hence, an accurate and effective classification of such samples is a challenge. Machine learning techniques have been broadly utilized to build substantial and precise classification models. This paper proposes a new classification technique for gene expression data, which is calle...

Bayesian State-Space Modeling in Gene Expression Data Analysis: An Application with Biomarker Prediction.

Background and ObjectiveBayesian State Space models are recent advancement in stochastic modeling which capture the randomness of a hidden background process by scrutinizing the prior knowledge and likelihood of observed data. This article elucidate the scope of Bayesian state space modeling on predicting the future expression values of a longitudinal micro array data. Methods The study conveniently makes use of longitudinally collected clinical trial data (GSE30531) from NCBI Gene Expression Omnibus (GEO) ...

Mining data and metadata from the gene expression omnibus.

Publicly available gene expression datasets deposited in the Gene Expression Omnibus (GEO) are growing at an accelerating rate. Such datasets hold great value for knowledge discovery, particularly when integrated. Although numerous software platforms and tools have been developed to enable reanalysis and integration of individual, or groups, of GEO datasets, large-scale reuse of those datasets is impeded by minimal requirements for standardized metadata both at the study and sample levels as well as uniform...

Inferring gene expression networks with hubs using a degree weighted Lasso approach.

Genome-scale gene networks contain regulatory genes called hubs that have many interaction partners. These genes usually play an essential role in gene regulation and cellular processes. Despite recent advancements in high-throughput technology, inferring gene networks with hub genes from high-dimensional data still remains a challenging problem. Novel statistical network inference methods are needed for efficient and accurate reconstruction of hub networks from high-dimensional data.

Conditional generative adversarial network for gene expression inference.

The rapid progress of gene expression profiling has facilitated the prosperity of recent biological studies in various fields, where gene expression data characterizes various cell conditions and regulatory mechanisms under different experimental circumstances. Despite the widespread application of gene expression profiling and advances in high-throughput technologies, profiling in genome-wide level is still expensive and difficult. Previous studies found that high correlation exists in the expression patte...

Evaluation of Reference Genes for Normalization of RT-qPCR Gene Expression Data for Trichoplusia ni Cells During Antheraea pernyi (Lepidoptera: Saturniidae) Multicapsid Nucleopolyhedrovirus (AnpeNPV) Infection.

Baculovirus infection impacts global gene expression in the host cell, including the expression of housekeeping genes. Evaluation of candidate reference genes during a viral infection will inform the selection of appropriate reference gene(s) for the normalization of expression data generated by Reverse Transcription Quantitative Real-timePolymerase Chain Reaction (RT-qPCR). Antheraea pernyi multicapsid nucleopolyhedrovirus (AnpeNPV) is able to infect the High Five cells (Tn-Hi5). In the present study, 10 c...

Learning Differential Module Networks Across Multiple Experimental Conditions.

Module network inference is a statistical method to reconstruct gene regulatory networks, which uses probabilistic graphical models to learn modules of coregulated genes and their upstream regulatory programs from genome-wide gene expression and other omics data. Here, we review the basic theory of module network inference, present protocols for common gene regulatory network reconstruction scenarios based on the Lemon-Tree software, and show, using human gene expression data, how the software can also be a...

Expression reflects population structure.

Population structure in genotype data has been extensively studied, and is revealed by looking at the principal components of the genotype matrix. However, no similar analysis of population structure in gene expression data has been conducted, in part because a naïve principal components analysis of the gene expression matrix does not cluster by population. We identify a linear projection that reveals population structure in gene expression data. Our approach relies on the coupling of the principal compone...

A Growing Toolbox to Image Gene Expression in Single Cells: Sensitive Approaches for Demanding Challenges.

The spatiotemporal regulation of gene expression is key to many biological processes. Recent imaging approaches opened exciting perspectives for understanding the intricate mechanisms regulating RNA metabolism, from synthesis to decay. Imaging techniques allow their observation at high spatial and temporal resolution, while keeping cellular morphology and micro-environment intact. Here, we focus on approaches for imaging single RNA molecules in cells, tissues, and embryos. In fixed cells, the rapid developm...

Conducting gene set tests in meta-analyses of transcriptome expression data.

Research synthesis, e.g. by meta-analysis, is more and more considered in the area of high-dimensional data from molecular research such as gene and protein expression data, especially because most studies and experiments are performed with very small sample sizes. In contrast to most clinical and epidemiological trials, raw data is often available for high-dimensional expression data. Therefore, direct data merging followed by a joint analysis of selected studies can be an alternative to meta-analysis by p...

MiPanda: A Resource for Analyzing and Visualizing Next-Generation Sequencing Transcriptomics Data.

The Michigan Portal for the Analysis of NGS data portal (http://mipanda.org) is an open-access online resource that provides the scientific community with access to the results of a large-scale computational analysis of thousands of high-throughput RNA sequencing (RNA-seq) samples. The portal provides access to gene expression profiles, enabling users to interrogate expression of genes across myriad normal and cancer tissues and cell lines. From these data, tissue- and cancer-specific expression patterns ca...

Evidence for Weak Selective Constraint on Human Gene Expression.

Gene expression variation is a major contributor to phenotypic variation in human complex traits. Selection on complex traits may therefore be reflected in constraint on gene expression. Here, we explore the effects of stabilizing selection on -regulatory genetic variation in humans. We analyze patterns of expression variation at copy number variants and find evidence for selection against large increases in gene expression. Using allele-specific expression (ASE) data, we further show evidence of selection ...

LST1: A multifunctional gene encoded in the MHC class III region.

The LST1 gene is located in the MHC class III cluster between the MHC class I and II regions. While most genes in this cluster have been sufficiently characterised, a definitive function and expression pattern for LST1 still remains elusive. In the present review we describe its promotor, gene organisation, splice variants and expression in human tissues, cell lines and cancer. We focus on LST1 expression in inflammation and discuss known correlations with autoimmune diseases and cancer. Current data on LST...

Bayesian Data Fusion of Gene Expression and Histone Modification Profiles for Inference of Gene Regulatory Network.

Accurately reconstructing gene regulatory networks (GRNs) from high-throughput gene expression data has been a major challenge in systems biology for decades. Many approaches have been proposed to solve this problem. However, there is still much room for the improvement of GRN inference. Integrating data from different sources is a promising strategy. Epigenetic modifications have a close relationship with gene regulation. Hence, epigenetic data such as histone modification profiles can provide useful infor...

FTO mRNA expression in the lower quartile is associated with bad prognosis in clear cell renal cell carcinoma based on TCGA data mining.

Fat mass and obesity associated (FTO) is a protein-coding gene, also known as the obesity gene. It has been reported previously to be associated with a variety of malignant cancers, such as breast, thyroid and acute myeloid leukemia. The aim of the present study was to investigate the FTO mRNA expression in human clear cell renal cell carcinoma and its clinical value. FTO mRNA expression and its prognostic value were investigated by bioinformatic analysis of the data from The Cancer Genome Atlas (TCGA, http...

Evaluation of reference genes for RT-qPCR analysis in wild and cultivated Cannabis.

RT-qPCR has been widely used for gene expression analysis in recent years. The accuracy of this technique largely depends on the selection of suitable reference genes. In order to facilitate gene expression analysis in wild and cultivated Cannabis, the expression stability of seven candidate reference genes (ACT2, 18S rRNA, GAPDH, UBQ, TUB, PP2A and EF1α) were assessed in leaves samples of different development stages and different organs of both wild and cultivated Cannabis in the present study. Their exp...


Advertisement
Quick Search
Advertisement
Advertisement