AIMC Topic: Data Mining

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Searches for randomized controlled trials of drugs in MEDLINE and EMBASE using only generic drug names compared with searches applied in current practice in systematic reviews.

Research synthesis methods
BACKGROUND: It is unclear which terms should be included in bibliographic searches for randomized controlled trials (RCTs) of drugs, and identifying relevant drug terms can be extremely laborious. The aim of our analysis was to determine whether a bi...

Using Semantic Association to Extend and Infer Literature-Oriented Relativity Between Terms.

IEEE/ACM transactions on computational biology and bioinformatics
Relative terms often appear together in the literature. Methods have been presented for weighting relativity of pairwise terms by their co-occurring literature and inferring new relationship. Terms in the literature are also in the directed acyclic g...

Mining Gene Regulatory Networks by Neural Modeling of Expression Time-Series.

IEEE/ACM transactions on computational biology and bioinformatics
Discovering gene regulatory networks from data is one of the most studied topics in recent years. Neural networks can be successfully used to infer an underlying gene network by modeling expression profiles as times series. This work proposes a novel...

BMExpert: Mining MEDLINE for Finding Experts in Biomedical Domains Based on Language Model.

IEEE/ACM transactions on computational biology and bioinformatics
With the rapid development of biomedical sciences, a great number of documents have been published to report new scientific findings and advance the process of knowledge discovery. By the end of 2013, the largest biomedical literature database, MEDLI...

Mining nutrigenetics patterns related to obesity: use of parallel multifactor dimensionality reduction.

International journal of bioinformatics research and applications
This paper aims to enlighten the complex etiology beneath obesity by analysing data from a large nutrigenetics study, in which nutritional and genetic factors associated with obesity were recorded for around two thousand individuals. In our previous ...

Learning multiple distributed prototypes of semantic categories for named entity recognition.

International journal of data mining and bioinformatics
The scarcity of large labelled datasets comprising clinical text that can be exploited within the paradigm of supervised machine learning creates barriers for the secondary use of data from electronic health records. It is therefore important to deve...

Sequence based human leukocyte antigen gene prediction using informative physicochemical properties.

International journal of data mining and bioinformatics
Prediction of different classes within the human leukocyte antigen (HLA) gene family can provide insight into the human immune system and its response to viral pathogens. Therefore, it is desirable to develop an efficient and easily interpretable met...

Exploiting multi-layered vector spaces for signal peptide detection.

International journal of data mining and bioinformatics
Analysing and classifying sequences based on similarities and differences is a mathematical problem of escalating relevance and importance in many scientific disciplines. One of the primary challenges in applying machine learning algorithms to sequen...