High-throughput screening (HTS) is a common technique for both drug discovery and basic research, but researchers often struggle with how best to derive hits from HTS data. While a wide range of hit identification techniques exist, little information is available about their sensitivity and specificity, especially in comparison to each other. To address this, we have developed the open-source NoiseMaker software tool for generation of realistically noisy virtual screens.
Deep sequencing of small RNAs has become a routine process in recent years, but no dedicated viewer is as yet available to explore the sequence features simultaneously along with secondary structure and gene expression of microRNA (miRNA). We present a highly interactive application that visualizes the sequence alignment, secondary structure and normalized read counts in synchronous multipanel windows.
We introduce GO-Elite, a flexible and powerful pathway analysis tool for a wide array of species, identifiers (IDs), pathways, ontologies and gene sets. In addition to the Gene Ontology (GO), GO-Elite allows the user to perform over-representation analysis on any structured ontology annotations, pathway database or biological IDs (e.g. gene, protein or metabolite). GO-Elite exploits the structured nature of biological ontologies to report a minimal set of non-overlapping terms. The results can be visualized on WikiPathways or as networks.
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.
A fast growing number of non-coding RNAs have recently been discovered to play essential roles in many cellular processes. Similar to proteins, understanding the functions of these active RNAs requires methods for analyzing their tertiary structures. However, in contrast to the wide range of structure-based approaches available for proteins, there is still a lack of methods for studying RNA structures.
In recent times, information on miRNAs and their binding sites is gaining momentum. Therefore, there is interest in the development of tools extracting miRNA related information from known literature. Hence, we describe GeneAFinder and miRAFinder scripts (open source) developed using python programming for the semi-automatic extraction and arrangement of updated information on miRNAs, genes and additional data from published article abstracts in PubMed. The scripts are suitable for custom modification as per requirement.
In this note, we propose an R function named NqA (Normalization qPCR Array, where qPCR is quantitative real-time polymerase chain reaction) suitable for the identification of a set of microRNAs (miRNAs) to be used for data normalization in view of subsequent validation studies with qPCR data.
High-throughput measurement technologies have triggered a rise in large-scale cancer studies containing multiple levels of molecular data. While there are a number of efficient methods to analyze individual data types, there are far less that enhance data interpretation after analysis. We present the R package Director, a dynamic visualization approach to linking and interrogating multiple levels of molecular data after analysis for clinically meaningful, actionable insights.
This report describes the miRQuest - a novel middleware available in a Web server that allows the end user to do the miRNA research in a user-friendly way. It is known that there are many prediction tools for microRNA (miRNA) identification that use different programming languages and methods to realize this task. It is difficult to understand each tool and apply it to diverse datasets and organisms available for miRNA analysis. miRQuest can easily be used by biologists and researchers with limited experience with bioinformatics.
The miRBase database is the central and official repository for miRNAs and the current release is miRBase version 21.0. Name changes in different miRBase releases cause inconsistencies in miRNA names from version to version. When working with only a small number of miRNAs the translation can be done manually. However, with large sets of miRNAs, the necessary correction of such inconsistencies becomes burdensome and error-prone.
Our database aim to make it easy for researchers to find the right tools or data source for their own specific study in miRNA field. Now we have collect >1000 tools. This database will update when every new 100 tools add in. Last update time 22nd April, 2018 (v1.2).
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