AIMC Topic: Gene Expression Profiling

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Clinical intelligence: New machine learning techniques for predicting clinical drug response.

Computers in biology and medicine
Predicting the response, or sensitivity, of a clinical drug to a specific cancer type is an important research problem. By predicting the clinical drug response correctly, clinicians are able to understand patient-to-patient differences in drug sensi...

Discerning novel splice junctions derived from RNA-seq alignment: a deep learning approach.

BMC genomics
BACKGROUND: Exon splicing is a regulated cellular process in the transcription of protein-coding genes. Technological advancements and cost reductions in RNA sequencing have made quantitative and qualitative assessments of the transcriptome both poss...

Integrative Gene Selection on Gene Expression Data: Providing Biological Context to Traditional Approaches.

Journal of integrative bioinformatics
The advance of high-throughput RNA-Sequencing techniques enables researchers to analyze the complete gene activity in particular cells. From the insights of such analyses, researchers can identify disease-specific expression profiles, thus understand...

Feature selection and tumor classification for microarray data using relaxed Lasso and generalized multi-class support vector machine.

Journal of theoretical biology
At present, the study of gene expression data provides a reference for tumor diagnosis at the molecular level. It is a challenging task to select the feature genes related to the classification from the high-dimensional and small-sample gene expressi...

Distillation of the clinical algorithm improves prognosis by multi-task deep learning in high-risk Neuroblastoma.

PloS one
We introduce the CDRP (Concatenated Diagnostic-Relapse Prognostic) architecture for multi-task deep learning that incorporates a clinical algorithm, e.g., a risk stratification schema to improve prognostic profiling. We present the first application ...

Effect of potential probiotic Leuconostoc mesenteroides FB111 in prevention of cholesterol absorption by modulating NPC1L1/PPARα/SREBP-2 pathways in epithelial Caco-2 cells.

International microbiology : the official journal of the Spanish Society for Microbiology
Mustard kimchi consumption reduces cholesterol levels in rats. To identify lactic acid bacteria (LAB) in kimchi which exert this effect, 20 LAB isolates were evaluated for cholesterol reduction in an in vitro screen. The FB111 strain showed the highe...

Found In Translation: a machine learning model for mouse-to-human inference.

Nature methods
Cross-species differences form barriers to translational research that ultimately hinder the success of clinical trials, yet knowledge of species differences has yet to be systematically incorporated in the interpretation of animal models. Here we pr...

Machine learning based classification of cells into chronological stages using single-cell transcriptomics.

Scientific reports
Age-associated deterioration of cellular physiology leads to pathological conditions. The ability to detect premature aging could provide a window for preventive therapies against age-related diseases. However, the techniques for determining cellular...

Artificial Neural Network to Predict Varicocele Impact on Male Fertility through Testicular Endocannabinoid Gene Expression Profiles.

BioMed research international
The relationship between varicocele and fertility has always been a matter of debate because of the absence of predictive clinical indicators or molecular markers able to define the severity of this disease. Even though accumulated evidence demonstra...

SIFR annotator: ontology-based semantic annotation of French biomedical text and clinical notes.

BMC bioinformatics
BACKGROUND: Despite a wide adoption of English in science, a significant amount of biomedical data are produced in other languages, such as French. Yet a majority of natural language processing or semantic tools as well as domain terminologies or ont...