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Explore molecular interactions across cancer types with CancerNet

Cancer is a complex disease characterized by a large number of molecular interaction alterations. Knowledge of molecular interactions is quite useful for discovering the functions of molecules and the processes they are involved in. However, there is little systematic insight into the nature and scale of the potential interactions in human cancers.     To solve this gap, Dr. Ming Chen and his colleagues from the Institute of Bioinformatics in Zhejiang University constructed CancerNet, a database for decoding multilevel molecular interactions across diverse cancer types. Here, they describe the features of CancerNet. The CancerNet database   CancerNet aims to provide cancer-specific molecular interaction networks across multiple cancer types. It includes 33 human cancer types. The interactions contain protein-protein interactions (PPIs), miRNA–target …

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qPCR techniques and analysis software tools

Quantitative real-time polymerase chain reaction (qPCR) is widely used for the detection of specific nucleic acids, measurement of RNA transcript abundance and validation of high-throughput experimental results. While high-throughput sequencing (HTS) has revolutionized the fields of genomics and transcriptomics, qPCR techniques have evolved and can now be performed in a high-throughput fashion. Introduction qPCR is an easy-to-perform technique to evaluate the relative (or absolute) expression of genes as compared to each other and/or a reference. Traditional qPCR is often used to validate results from gene arrays or HTS, as it is more precise, rapid to perform, and cheap.   Recently, new technologies have been developed to increase the number of genes that can be tested simultaneously. Next generation qPCR platforms …

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Visualize differential gene expression with ViDGER

Differential gene expression (DGE) analysis is one of the most common applications of RNA-seq data. This process allows for the elucidation of differentially expressed genes (DEGs) across two or more conditions. Interpretation of the DGE results can be non-intuitive and time-consuming due to the variety of formats based on the tool of choice and the numerous pieces of information provided in these results files. To address this challenge, Adam McDermaid and his colleagues from South Dakota State University have developed ViDGER. Here, they present their tool and its main features.   Interpretation and Visualization of Differential Gene Expression through ViDGER   One of the most straightforward ways to gain a broader understanding of the tens-of-thousands of pieces of information generated …

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Choose and use the right license for your software tool

Whether you are a software developer wishing to distribute your tool, or a user/programmer in need to use and/or modify a tool, you are confronted to licensing. Software licenses govern the use or redistribution of a software under specific laws. Two common categories for software under copyright law (which grants the licensee specific rights) are proprietary software and free and open source software (FOSS). The main difference between proprietary and FOSS license is the granting of rights to modify and re-use a software by a customer: FOSS software licenses both rights to the customer, while proprietary software does not license these rights (Wikipedia).   Software licenses on OMICtools   Following the general tendency to develop more open-source software, more than …

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Credit your work and enter to win a pass for a congress

You designed a tool or performed specific tasks in software development? Spread the word! Credit your expertise with badges and enter to win a pass for a congress (and others exciting prizes). To participate, all you need to do is badge your contribution on the bioinformatics tools we reference.  Don’t hang around, the contest ends the 11th May. How does the contest work? Sign in to your account (or sign up for free if you aren’t already a member). Find the tools you designed (or contributed to design): use the search engine and filters to rapidly locate your project Click on the “set my contributions” button  to add badges Why are badges important? Badges are the best way to earn …

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Explore gene-expression datasets with the Omics Dashboard

The advent of omics technologies has fostered the generation of a flood of complex, high-resolution datasets, the analysis of which remains a major hurdle and requires conversion into actionable biological knowledge. To address this challenge, Peter Karp and his colleagues from the SRI Bioinformatics Research Group have developed the Omics Dashboard within the BioCyc.org website. Here, they present their tool and its main features. The Omics Dashboard The Dashboard provides a multi-level visual read out of an expression dataset, from the cellular level to the gene level.  The user can probe their data in a fast and intuitive manner to gain a deep understanding of the data at multiple biological levels.   At the highest echelon (Figure 1) the Dashboard provides …

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Best bioinformatics software for MS-based proteomics analysis

Proteomics are the next step after genomics and transcriptomics to study biological systems. However, analyzing the proteome is much more difficult than the genome or transcriptome, because each cell expresses its own set of proteins. Mass spectrometry (MS) has emerged as the most important and popular tool to identify, characterize, and quantify proteins and their post-translational modifications with high throughput and on a large scale (Zhang et al.). To help you perform your experiments in the best conditions, we asked the OMICtools community to choose the best MS-based untargeted proteomics analysis tools. LC-MS based untargeted proteomics Two-dimension liquid-chromatography (LC) coupled with mass-spectrometry (LC-MS) is the leading technology for high-throughput proteomics. LC is used to separate proteins from different samples in parallel, and …

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Finding scientific resources with semantic search engines

  The exponential growth of the number of biological studies over the past decade has created an enormous challenge to make effective use of the accumulated information. Owing to this size, simple web-style text search engines are often not yielding the best results and a lot of important information remains buried in the masses of text (Doms, 2005). Semantic technologies have been introduced for better question answering and faster literature exploration (Doms, 2008). They use ontologies to give an overview over large query results and guide scientists for discoveries. Starting your research in biology but don’t know which platform to use to find impactful studies? Here is a list of useful resources you will love using to retrieve articles and …

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