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K562 Cells

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[Effects of Sinopodophyllum hexundrum on apoptosis in K562 cells].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: To investigate the effects of Sinopodophyllum hexundrum on apoptosis in K562 cells.

Identification of active transcriptional regulatory elements from GRO-seq data.

Nature methods
Modifications to the global run-on and sequencing (GRO-seq) protocol that enrich for 5'-capped RNAs can be used to reveal active transcriptional regulatory elements (TREs) with high accuracy. Here, we introduce discriminative regulatory-element detec...

LncRNA ontology: inferring lncRNA functions based on chromatin states and expression patterns.

Oncotarget
Accumulating evidences suggest that long non-coding RNAs (lncRNAs) perform important functions. Genome-wide chromatin-states area rich source of information about cellular state, yielding insights beyond what is typically obtained by transcriptome pr...

Cytopathological image analysis using deep-learning networks in microfluidic microscopy.

Journal of the Optical Society of America. A, Optics, image science, and vision
Cytopathologic testing is one of the most critical steps in the diagnosis of diseases, including cancer. However, the task is laborious and demands skill. Associated high cost and low throughput drew considerable interest in automating the testing pr...

Imputation for transcription factor binding predictions based on deep learning.

PLoS computational biology
Understanding the cell-specific binding patterns of transcription factors (TFs) is fundamental to studying gene regulatory networks in biological systems, for which ChIP-seq not only provides valuable data but is also considered as the gold standard....

The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology.

Oncotarget
Recent advances in deep learning and specifically in generative adversarial networks have demonstrated surprising results in generating new images and videos upon request even using natural language as input. In this paper we present the first applic...

Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Regulatory sequences are not solely defined by their nucleic acid sequence but also by their relative distances to genomic landmarks such as transcription start site, exon boundaries or polyadenylation site. Deep learning has become the a...