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View article: PHEE: A Dataset for Pharmacovigilance Event Extraction from Text
PHEE: A Dataset for Pharmacovigilance Event Extraction from Text Open
The PHEE dataset contains over 5,000 finely annotated pharmacovigilance events from public medical case reports. Two types of events, the adverse events and the potential therapeutic events, are annotated. For each event, we annotate the e…
View article: PHEE: A Dataset for Pharmacovigilance Event Extraction from Text
PHEE: A Dataset for Pharmacovigilance Event Extraction from Text Open
The PHEE dataset contains over 5,000 finely annotated pharmacovigilance events from public medical case reports. Two types of events, the adverse events and the potential therapeutic events, are annotated. For each event, we annotate the e…
View article: PHEE: A Dataset for Pharmacovigilance Event Extraction from Text
PHEE: A Dataset for Pharmacovigilance Event Extraction from Text Open
The PHEE dataset contains over 5,000 finely annotated pharmacovigilance events from public medical case reports. Two types of events, the adverse events and the potential therapeutic events, are annotated. For each event, we annotate the e…
View article: Interpretable bilinear attention network with domain adaptation improves drug-target prediction
Interpretable bilinear attention network with domain adaptation improves drug-target prediction Open
Predicting drug-target interaction is key for drug discovery. Recent deep learning-based methods show promising performance but two challenges remain: (i) how to explicitly model and learn local interactions between drugs and targets for b…
View article: PHEE: A Dataset for Pharmacovigilance Event Extraction from Text
PHEE: A Dataset for Pharmacovigilance Event Extraction from Text Open
The primary goal of drug safety researchers and regulators is to promptly identify adverse drug reactions. Doing so may in turn prevent or reduce the harm to patients and ultimately improve public health. Evaluating and monitoring drug saf…
View article: Effective expression analysis using gene interaction matrices and convolutional neural networks
Effective expression analysis using gene interaction matrices and convolutional neural networks Open
Artificial intelligence recently experienced a renaissance with the advancement of convolutional neural networks (CNNs). CNNs require spatially meaningful matrices ( e.g ., image data) with recurring patterns, limiting its applicability to…
View article: Potential miRNA Target Sites in the 3′ UTRs of Selected Genes
Potential miRNA Target Sites in the 3′ UTRs of Selected Genes Open
Nucleotide sequence conservation between the 3′ UTRs of human and the closest mouse or rat orthologous genes is averaged for each block of 40 base pairs (long rectangles; white indicates 0% identical nucleotides, black indicates 100% ident…
View article: Noncoding RNAs that associate with YB-1 alter proliferation in prostate cancer cells
Noncoding RNAs that associate with YB-1 alter proliferation in prostate cancer cells Open
The highly conserved, multifunctional YB-1 is a powerful breast cancer prognostic indicator. We report on a pervasive role for YB-1 in which it associates with thousands of nonpolyadenylated short RNAs (shyRNAs) that are further processed …
View article: Genome-Wide Transcript Profiling Reveals Novel Breast Cancer-Associated Intronic Sense RNAs
Genome-Wide Transcript Profiling Reveals Novel Breast Cancer-Associated Intronic Sense RNAs Open
Non-coding RNAs (ncRNAs) play major roles in development and cancer progression. To identify novel ncRNAs that may identify key pathways in breast cancer development, we performed high-throughput transcript profiling of tumor and normal ma…