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I would like to phase whole-genome datasets, some of which are single-end read datasets and some of which are paired-end datasets. Does anyone have experience with this? Should I simply generate a list of SNPs and feed it to existing phasing algorithms? Is there software that can take the raw read data into account (IE SNPs that appear on the same read)?
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Non-coding RNAs (ncRNAs) do not code for proteins but play important roles in numerous cellular processes including gene silencing, developmental pathways, and more. There are numerous types including microRNA (miRNA), long ncRNA (lncRNA), circular RNA (circRNA), and more. In this article, we discuss innovative ncRNA research and explore recent technological advancements that improve the study of ncRNAs.
Nobel Prize for MicroRNA Discovery
This week,...10-07-2024, 08:07 AM -
Metagenomics has improved the way researchers study microorganisms across diverse environments. Historically, studying microorganisms relied on culturing them in the lab, a method that limits the investigation of many species since most are unculturable1. Metagenomics overcomes these issues by allowing the study of microorganisms regardless of their ability to be cultured or the environments they inhabit. Over time, the field has evolved, especially with the advent...09-23-2024, 06:35 AM
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