Computational Tools

Here are links to several tools developed by the PMI SFA

RWR Toolkit – developed by the Computational Systems Biology team (David Kainer, J. Izaak Miller, Matthew Lane, Mikaela Cashman, Kyle Sullivan, Ashley Cliff, Jonathon Romero, Angelica Walker,  Daniel Jacobson).  This toolkit allows you to perform Random-walk with Restart analyses on multiplex networks in any species.  This includes the complete set of command-line and R tools. Reference (not currently available). 

DISCo-microbe – developed by Dana Carper.  Interested is setting up your own diverse, identifiable synthetic community? Design of an Identifiable Synthetic Community of Microbes (DISCo-microbe) is an easy-to-use command-line program, for creation of diverse communities of organisms that can be distinguished through next-generation sequencing technology.  Reference

amPEPpy – developed by Travis Lawrence.  amPEPpy is a Python 3 application that implements a random forest classifier for predicting antimicrobial peptide sequences using the Distribution descriptor set from the Global Protein Sequence Descriptors. amPEPpy has improved portability, increased accuracy relative to similar methods, and includes utilities for easily training and optimizing random forest classifiers on novel training data.  Reference

P Finder – developed by J. Chris Ellis.  P Finder is the only available algorithm that is capable of not only identifying the RNase P RNA for annotation but also differentiating among the five different RNase P RNA structural types (A, B, C, M, and T) with the option to select these data types for display in the final output.  Reference