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jQuery is a cross-platform JavaScript library designed to simplify the client-side scripting of HTML. [Source: Wikipedia ]

CSZ

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

During early vertebrate development, various small non-coding RNAs (sRNAs) such as MicroRNAs (miRNAs) and Piwi-interacting RNAs (piRNAs) are dynamically expressed for orchestrating the maternal-to-zygotic transition (MZT). Systematic analysis of expression profiles of zebrafish small RNAome will be greatly helpful for understanding the sRNA regulation during embryonic development.

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RiceATM

Submitted by ChenLiang on Mon, 01/09/2017 - 11:36

MicroRNAs (miRNAs) are known to play critical roles in plant development and stress-response regulation, and they frequently display multi-targeting characteristics. The control of defined rice phenotypes occurs through multiple genes; however, evidence demonstrating the relationship between agronomic traits and miRNA expression profiles is lacking. In this study, we investigated eight yield-related traits in 187 local rice cultivars and profiled the expression levels of 193 miRNAs in these cultivars using microarray analyses.

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CSCdb

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

Cancer stem cells (CSCs), which have the ability to self-renew and differentiate into various tumor cell types, are a special class of tumor cells. Characterizing the genes involved in CSCs regulation is fundamental to understand the mechanisms underlying the biological process and develop treatment methods for tumor therapy. Recently, much effort has been expended in the study of CSCs and a large amount of data has been generated. However, to the best of our knowledge, database dedicated to CSCs is not available until now.

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Tools4miRs

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

MiRNAs are short, non-coding molecules that negatively regulate gene expression and thereby play several important roles in living organisms. Dozens of computational methods for miRNA-related research have been developed, which greatly differ in various aspects. The substantial availability of difficult-to-compare approaches makes it challenging for the user to select a proper tool and prompts the need for a solution that will collect and categorize all the methods.

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dbPHCC

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

Hepatocellular carcinoma (HCC) is one of the most common malignant cancers with a poor prognosis. For decades, more and more biomarkers were found to effect on HCC prognosis, but these studies were scattered and there were no unified identifiers. Therefore, we built the database of prognostic biomarkers and models for hepatocellular carcinoma (dbPHCC).

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PlanTE-MIR DB

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

Transposable elements (TEs) comprise a major fraction of many plant genomes and are known to drive their organization and evolution. Several studies show that these repetitive elements have a prominent role in shaping noncoding regions of the genome such as microRNA (miRNA) loci, which are components of post-transcriptional regulation mechanisms.

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MicroTrout

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

Rainbow trout represent an important teleost research model and aquaculture species. As such, rainbow trout are employed in diverse areas of biological research, including basic biological disciplines such as comparative physiology, toxicology, and, since rainbow trout have undergone both teleost- and salmonid-specific rounds of genome duplication, molecular evolution. In recent years, microRNAs (miRNAs, small non-protein coding RNAs) have emerged as important posttranscriptional regulators of gene expression in animals.

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5
Average: 4.5 (2 votes)

BCCTBbp

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

BCCTBbp (http://bioinformatics.breastcancertissuebank.org) was initially developed as the data-mining portal of the Breast Cancer Campaign Tissue Bank (BCCTB), a vital resource of breast cancer tissue for researchers to support and promote cutting-edge research.

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miXGENE

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

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 this paper, we propose a random forest-based classifier that reduces this overfitting with the aid of prior knowledge in the form of a feature interaction network.

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