AIMC Topic: Transcriptome

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StressGenePred: a twin prediction model architecture for classifying the stress types of samples and discovering stress-related genes in arabidopsis.

BMC genomics
BACKGROUND: Recently, a number of studies have been conducted to investigate how plants respond to stress at the cellular molecular level by measuring gene expression profiles over time. As a result, a set of time-series gene expression data for the ...

Transcriptome analysis and identification of genes associated with chicken sperm storage duration.

Poultry science
The sperm storage tubules located in the mucosal folds of the uterovaginal junction (UVJ) are the primary site of sperm storage in chicken hens after natural mating or artificial insemination (AI). The short-term sperm storage (24 h after mating or A...

Discovery and annotation of novel microRNAs in the porcine genome by using a semi-supervised transductive learning approach.

Genomics
Despite the broad variety of available microRNA (miRNA) prediction tools, their application to the discovery and annotation of novel miRNA genes in domestic species is still limited. In this study we designed a comprehensive pipeline (eMIRNA) for miR...

Global transcriptome analysis reveals relevant effects at environmental concentrations of cypermethrin in honey bees (Apis mellifera).

Environmental pollution (Barking, Essex : 1987)
Cypermethrin is a frequently used insecticide in agriculture and households but its chronic and molecular effects are poorly known are . Here we describe effects of sublethal cypermethrin exposure on the global transcriptome in the brain of honey bee...

CDSeq: A novel complete deconvolution method for dissecting heterogeneous samples using gene expression data.

PLoS computational biology
Quantifying cell-type proportions and their corresponding gene expression profiles in tissue samples would enhance understanding of the contributions of individual cell types to the physiological states of the tissue. Current approaches that address ...

Approach for the Definition of radiomiRNomic Signatures for Breast Cancer Differential Diagnosis.

International journal of molecular sciences
UNLABELLED: Personalized medicine relies on the integration and consideration of specific characteristics of the patient, such as tumor phenotypic and genotypic profiling.

Four transcription profile-based models identify novel prognostic signatures in oesophageal cancer.

Journal of cellular and molecular medicine
Oesophageal cancer (ESCA) is a clinically challenging disease with poor prognosis and health-related quality of life. Here, we investigated the transcriptome of ESCA to identify high risk-related signatures. A total of 159 ESCA patients of The Cancer...

DeePathology: Deep Multi-Task Learning for Inferring Molecular Pathology from Cancer Transcriptome.

Scientific reports
Despite great advances, molecular cancer pathology is often limited to the use of a small number of biomarkers rather than the whole transcriptome, partly due to computational challenges. Here, we introduce a novel architecture of Deep Neural Network...

Molecular expression profiles of morphologically defined hippocampal neuron types: Empirical evidence and relational inferences.

Hippocampus
Gene and protein expressions are key determinants of cellular function. Neurons are the building blocks of brain circuits, yet the relationship between their molecular identity and the spatial distribution of their dendritic inputs and axonal outputs...