• RemeDB

    Tool to identify Bioremediation enzymes from
    Metagenomic Datasets.

Features

Interactive User-Interface

A hassle-free tool to predict bioremediation enzymes from metagenomic datasets

Downloads

Available for Linux platforms.

Robust and high speed

Features like hmm, rapsearch, transeq process metagenomic data at high-speeds

Categorized output

Predicted remediation enzymes are separately available in different folders.

Welcome to RemeDB

RemeDB aims at identifying Pollutant Degrading Enzymes (PDE) from metagenomic sequences.

Enables classification and prediction novel enzymes classes.

User interprtable outputs generated at lightning fast speed ( number of computer threads )

Enzymes associated with bioremediation were categorized under 3 categories:

> Hydrocarbon degrading enzymes

> Plastic degrading enzymes

> Dye degrading enzymes

Transeq

Method to convert the Input metagenomic sequences to protein sequences

Hmmer

Hmm based profile creation to predict remote homologs from translated input data.

Rapsearch

Reduced alaphabet based search tool to predict closely related homologs to the remediation enzymes

Screenshots

Downloads

Please click here to download Linux version

Contact us

member-4

Dr. G. Dharani

Scientist-F, NIOT. Email: dharani.niot@gov.in

member-1

Mr. R. Vijaya Raghavan

Project Scientist-1, NIOT. Email: vijay.niot@nic.in

member-2

Mr. Sai Hariharan

Senior Research Fellow (SRF), NIOT. Email: saihariharan.niot@nic.in

member-3

Dr. B. Karpaga Raja Sundari

Research Associate, NIOT. Email: sundari.niot@nic.in

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