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Precise cancer classification is a central challenge in clinical cancer research such as diagnosis, prognosis and metastasis prediction. Most existing cancer classification methods based on gene or metabolite biomarkers were limited to single genomics or metabolomics, and lacked integration and utilization of multiple 'omics' data. The accuracy and(More)
MicroRNAs (miRNAs) are a class of non-coding RNAs known to play important regulatory roles through targets, which can affect human cell proliferation, differentiation, and metabolism. Overlaps between different miRNA target prediction algorithms (MTPAs) are small, which limit the understanding of miRNA's biological functions. However, the overlaps increase(More)
The Tianshan mountain range is experiencing a notable environmental change as a result of global warming. In this paper; we adopt multiple remote sensing techniques to examine the diversified geophysical changes in the Tianshan; including glacier changes measured by Gravity Recovery and Climate Experiment (GRACE) and Ice, Cloud, and land Elevation Satellite(More)
The main purpose of this study is to propose, then analyze, and later test a spectral gradient algorithm for solving a convex minimization problem. The considered problem covers the matrix ℓ2,1-norm regularized least squares which is widely used in multi-task learning for capturing the joint feature among each task. To solve the problem, we firstly minimize(More)
While gene fusions have been increasingly detected by next-generation sequencing (NGS) technologies based methods in human cancers, these methods have limitations in identifying driver fusions. In addition, the existing methods to identify driver gene fusions ignored the specificity among different cancers or only considered their local rather than global(More)
Detecting and interpreting certain system-level characteristics associated with human population genetic differences is a challenge for human geneticists. In this study, we conducted a population genetic study using the HapMap genotype data to identify certain special Gene Ontology (GO) categories associated with high/low genetic difference among 11 Hapmap(More)
One of the challenging problems in drug discovery is to identify the novel targets for drugs. Most of the traditional methods for drug targets optimization focused on identifying the particular families of "druggable targets", but ignored their topological properties based on the biological pathways. In this study, we characterized the topological(More)
Metabolic pathway analysis is a popular strategy for comprehensively researching metabolites and genes of interest associated with specific diseases. However, the traditional pathway identification methods do not accurately consider the combined effect of these interesting molecules and neglects expression correlations or topological features embedded in(More)
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