Identification of neoantigens is a critical step in predicting response to checkpoint blockade therapy and design of personalized cancer vaccines. This is a cross-disciplinary challenge, involving genomics, proteomics, immunology, and computational a...
BACKGROUND: In recent years, biomedical ontologies have become important for describing existing biological knowledge in the form of knowledge graphs. Data mining approaches that work with knowledge graphs have been proposed, but they are based on ve...
As a crucial step of biological event extraction, event trigger identification has attracted much attention in recent years. Deep representation methods, which have the superiorities of less feature engineering and end-to-end training, show better pe...
BACKGROUND: In biomedical text mining, named entity recognition (NER) is an important task used to extract information from biomedical articles. Previously proposed methods for NER are dictionary- or rule-based methods and machine learning approaches...
Computational prediction of binding between neoantigen peptides and major histocompatibility complex (MHC) proteins can be used to predict patient response to cancer immunotherapy. Current neoantigen predictors focus on estimation of MHC binding aff...
BACKGROUND: Use of medication can cause adverse drug reactions (ADRs), unwanted or unexpected events, which are a major safety concern. Drug labels, or prescribing information or package inserts, describe ADRs. Therefore, systematically identifying A...
BMC medical informatics and decision making
Dec 23, 2019
BACKGROUND: Text mining and natural language processing of clinical text, such as notes from electronic health records, requires specific consideration of the specialized characteristics of these texts. Deep learning methods could potentially mitigat...
BMC medical informatics and decision making
Dec 21, 2019
BACKGROUND: Supervised machine learning algorithms have been a dominant method in the data mining field. Disease prediction using health data has recently shown a potential application area for these methods. This study ai7ms to identify the key tren...
Statistical data-mining (DM) and machine learning (ML) are promising tools to assist in the analysis of complex dataset. In recent decades, in the precision of agricultural development, plant phenomics study is crucial for high-throughput phenotyping...
Computational intelligence and neuroscience
Dec 19, 2019
Aspect-level sentiment classification aims to identify the sentiment polarity of a review expressed toward a target. In recent years, neural network-based methods have achieved success in aspect-level sentiment classification, and these methods fall ...