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QTG-Finder: A Machine-Learning Based Algorithm To Prioritize Causal Genes of Quantitative Trait Loci in Arabidopsis and Rice.
G3 (Bethesda, Md.)
Oct 7, 2019
Linkage mapping is one of the most commonly used methods to identify genetic loci that determine a trait. However, the loci identified by linkage mapping may contain hundreds of candidate genes and require a time-consuming and labor-intensive fine ma...
Siamese Neural Networks for User Identity Linkage Through Web Browsing.
IEEE transactions on neural networks and learning systems
Aug 13, 2019
Linking online identities of users among countless heterogeneous network services on the Internet can provide an explicit digital representation of users, which can benefit both research and industry. In recent years, user identity linkage (UIL) thro...
Prediction of ATP-binding sites in membrane proteins using a two-dimensional convolutional neural network.
Journal of molecular graphics & modelling
Jul 15, 2019
Membrane proteins, the most important drug targets, account for around 30% of total proteins encoded by the genome of living organisms. An important role of these proteins is to bind adenosine triphosphate (ATP), facilitating crucial biological proce...
mACPpred: A Support Vector Machine-Based Meta-Predictor for Identification of Anticancer Peptides.
International journal of molecular sciences
Apr 22, 2019
Anticancer peptides (ACPs) are promising therapeutic agents for targeting and killing cancer cells. The accurate prediction of ACPs from given peptide sequences remains as an open problem in the field of immunoinformatics. Recently, machine learning ...
Webcrawling and machine learning as a new approach for the spatial distribution of atmospheric emissions.
PloS one
Jul 16, 2018
In this study we apply two methods for data collection that are relatively new in the field of atmospheric science. The two developed methods are designed to collect essential geo-localized information to be used as input data for a high resolution e...
pLoc-mVirus: Predict subcellular localization of multi-location virus proteins via incorporating the optimal GO information into general PseAAC.
Gene
Jul 18, 2017
Knowledge of subcellular locations of proteins is crucially important for in-depth understanding their functions in a cell. With the explosive growth of protein sequences generated in the postgenomic age, it is highly demanded to develop computationa...
Extracting microRNA-gene relations from biomedical literature using distant supervision.
PloS one
Mar 6, 2017
Many biomedical relation extraction approaches are based on supervised machine learning, requiring an annotated corpus. Distant supervision aims at training a classifier by combining a knowledge base with a corpus, reducing the amount of manual effor...
Expansion of the Gene Ontology knowledgebase and resources.
Nucleic acids research
Nov 29, 2016
The Gene Ontology (GO) is a comprehensive resource of computable knowledge regarding the functions of genes and gene products. As such, it is extensively used by the biomedical research community for the analysis of -omics and related data. Our conti...
SNooPer: a machine learning-based method for somatic variant identification from low-pass next-generation sequencing.
BMC genomics
Nov 14, 2016
BACKGROUND: Next-generation sequencing (NGS) allows unbiased, in-depth interrogation of cancer genomes. Many somatic variant callers have been developed yet accurate ascertainment of somatic variants remains a considerable challenge as evidenced by t...
Ontobee: A linked ontology data server to support ontology term dereferencing, linkage, query and integration.
Nucleic acids research
Oct 12, 2016
Linked Data (LD) aims to achieve interconnected data by representing entities using Unified Resource Identifiers (URIs), and sharing information using Resource Description Frameworks (RDFs) and HTTP. Ontologies, which logically represent entities and...
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