Using data pipelining tools

Pipelining tools


Pipelining tools can be thought of as graphical scripting methods: tying together diverse applications to perform tasks. They are thus very suited to cheminformatics data mining. Two of the most widely used packages are Pipeline Pilot and Knime .

Knime Introduction

The video below gives the some basic introduction to Knime and how does it works . It is not possible to learn everything in a single course at once. You need to keep on using it and the ask the community for help .



Designed for new KNIME users, the webinar will show how to access the applications, install any needed extensions for extra functionality you might need, and finally how to use the applications on YOUR data.



Below Abhik shows how to use Knime in Chemical informatics cases . He shows some uses in cheminformatics and more videos on this would be added later as the course proceeds. The links to the Knime workflows are given at Abhik's git account .



Here is the link to the workflow of the above tutorial.

There is some quick start information and a forum available at the KNIME website and KNIMEtech. A pdf version of the quickstart guide can be found here.

Abhik Discusses about three different workflows on Similarity search, Activity Cliffs and Scaffold Enrichment .

Molecular scaffolds or frameworks are generated by removing all the substituents from the rings and from the linkers between the rings , forming molecular frameworks called the Bemis-Murcko scaffolds. Pharmacist's are interested on scaffold distributions, the degree of scaffold diversity, and the occurrence of overlap between scaffolds contained in compounds at different pharmaceutical development stages. Then after selecting scaffolds the next step is to identify relationship between molecular selectivity and target families or individual targets at scaffold level. Here is the Phd thesis of Yu hu who has done extensive work on scaffolds.



Video below shows how Knime can be used for Predictive Modeling Purposes. The Videos describes about the Random Forest Model and SVM with Cross validation and viewing the results.



Integrating Knime and R for Modeling purposes

Video below Abhik discusses how you can integrate R within Knime for modeling purposes. It also describes workflow QSAR workflow in Knime using R.





Knime Workflows are given at my github

Online Material


KNIME is easy to use and fast to learn. Find out how to install KNIME and build your first workflow. Check our FAQ for frequently asked questions.
Learn more about advanced usage of KNIME and its wide range of features. The learning hub is a collection of pointers to more material and our documentation section explains more advanced usage of KNIME in detail.
Don't miss any of our famous webinars! They are a great source of learning on specific topics. KNIME also offers training courses for data analysis, reporting, text mining, and much more. Find the nearest course in place and time!
KNIME is through its modular API, easily extensible. Learn how to build your own customized KNIME nodes.

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