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Protein–Protein Interaction extraction (PPIe) from biomedical literatures is an important task in biomedical text mining and has achieved desirable results on the annotated datasets. However, the traditional machine learning methods on PPIe suffer badly from vocabulary gap and data sparseness, which weakens classification performance. In this work, an approach capturing external information from the...
We use Human Microbiome Project (HMP) cohort (Peterson et al., 2009) to infer personalized oral microbial networks of healthy individuals. To determine clustering of individuals with similar microbial profiles, co-regularized spectral clustering algorithm is applied to the dataset. For each cluster we discovered, we compute co-occurrence relationships among the microbial species that determine microbial...
A network motif is defined as an over-represented subgraph pattern in a network. Network motif based techniques have been widely applied in analyses of biological networks such as transcription regulation networks (TRNs), protein–protein interaction networks (PPIs), and metabolic networks. The detection of network motifs involves the computationally expensive enumeration of subgraphs, NP-complete...
miRNA is known to regulate up to several hundreds coding genes, thus the integrated analysis of miRNA and mRNA expression data is an important problem. Unfortunately, the integrated analysis is challenging since it needs to consider expression data of two different types, miRNA and mRNA, and target relationship between miRNA and mRNA is not clear, especially when microarray data is used. Fortunately,...
Metallothionein-III (MT-III) displays neuro-inhibitory activity and is involved in the repair of neuronal damage. An altered expression level of MT-III suggests that it could be a mitigating factor in Alzheimer’s disease (AD) neuronal dysfunction. Currently there are limited marketed drugs available against MT-III. The inhibitors are mostly pseudo-peptide based with limited ADMET. In our present study,...
To get a better understanding of the ongoing in situ environmental changes preceding the brain tumorigenesis, we assessed cerebrospinal fluid (CSF) proteome profile changes in a glioma rat model in which brain tumor invariably developed after a single in utero exposure to the neurocarcinogen ethylnitrosourea (ENU). Computationally, the CSF proteome profile dynamics during the tumorigenesis can be...
Predicting drug–target interaction using computational approaches is an important step in drug discovery and repositioning. To predict whether there will be an interaction between a drug and a target, most existing methods identify similar drugs and targets in the database. The prediction is then made based on the known interactions of these drugs and targets. This idea is promising. However, there...
Multi-biomarker panels can capture the nonlinear synergy among biomarkers and they are important to aid in the early diagnosis and ultimately battle complex diseases. However, identification of these multi-biomarker panels from case and control data is challenging. For example, the exhaustive search method is computationally infeasible when the data dimension is high. Here, we propose a novel method,...
Essential proteins play a crucial role in cellular survival and development process. Experimentally, essential proteins are identified by gene knockouts or RNA interference, which are expensive and often fatal to the target organisms. Regarding this, an alternative yet important approach to essential protein identification is through computational prediction. Existing computational methods predict...
The 3′ untranslated region (3′ UTR) of mRNA contains elements that play regulatory roles in polyadenylation, localization, translation efficiency, and mRNA stability. Despite the significance of the 3′ UTR, there is no popular method for annotating 3′ UTRs and for profiling their isoforms. Recently, poly(A)-position profiling by sequencing (3P-seq) and other similar methods have successfully been...
Whole exome sequencing (WES) and RNA sequencing (RNA-Seq) are two main platforms used for next-generation sequencing (NGS). While WES is primarily for DNA variant discovery and RNA-Seq is mainly for measurement of gene expression, both can be used for detection of genetic variants, especially single nucleotide variants (SNVs). How consistently variants can be detected from WES and RNA-Seq has not...
Contemporary molecular biology deals with wide and heterogeneous sets of measurements to model and understand underlying biological processes including complex diseases. Machine learning provides a frequent approach to build such models. However, the models built solely from measured data often suffer from overfitting, as the sample size is typically much smaller than the number of measured features...
In microarray analysis, biclustering is used to find the maximal subsets of rows and columns satisfying some coherence criteria. The found submatrices are usually called as biclusters. On one hand, different criteria would help to find different types of biclusters, thus the definition of coherence criterion is critical to the biclustering method. On the other hand, qualitative criteria result to...
Annotating and understanding the function of proteins and other elements in a genome can be difficult in the absence of a well-studied and evolutionarily close relative. The causative agent of malaria, one of the oldest and most deadly global infectious diseases, is a good example of this problem. The burden of malaria is huge and there is a pressing need for new, more effective antimalarial strategies...
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