Mirlot Files

The interactive file manager requires Javascript. Please enable it or use sftp or scp.
You may still browse the files here.

Name	Modified	Size
Sample Input-Output	2011-09-03
protocol.pdf	2011-11-12	168.2 kB
tcgapathwayanalysis.zip	2011-09-03	221.5 kB
Totals: 3 Items		389.7 kB

Other Useful Business Software

$300 Free Credits to Build on Google Cloud

New customers can spin up VMs, build with AI, and query data at no cost.

Put your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.

Start Free

Veeam Data Platform v13.1 - Get Your Free Trial

Secure by design, portable by default. Recover clean, fast, anywhere. Start a free trial.

Try Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.

Try it Free

$300 Free Credits to Build on Google Cloud

New customers can spin up VMs, build with AI, and query data at no cost.

Put your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.

Start Free

Recommended Projects

sRNAWorkbench
The UEA sRNA Workbench
Scanpy
Single-cell analysis in Python
Crosshub
Multi-way analysis of The Cancer Genome Atlas (TCGA) project datasets
miRComb
This R package combines biological information (expression data) with theoretical information (miRNA target prediction databases) in order to obtain a curated list of potential miRNA-mRNA interaction pairs.
SRICATs
MicroRNAs (miRNAs) are of significance in tuning and buffering gene expression. Despite abundant analysis tools have been developed in the last two decades, plant miRNA identification from next-generation sequencing (NGS) data remains challenging. Here present a user-friendly pure Java-based software package, SRICATs, which enable researchers to perform all steps of plant miRNA analysis based on convolutional neural network methods. SRICATs outperforms currently popular software tools on the test data from five plant species: Oryza sativa, Arabidopsis thaliana, Sorghum bicolor, Chlamydomonas reinhardtii and Physcomitrella patens.