In Computational Biology, one of the most popular research is to find co-relation between bacteria, viruses and diseases by using different text mining techniques and finding relationship by extracting key words from different texts available.
Example: Weka (machine learning tool) can be used to find the occurrences of key words (biological) in different texts files.
I was wondering if someone can tell me how many tools are there such as Weka to do the same job?
Which one is better or what are the pros and cons of each?
Hello Somdip Dey,
I believe you will find these tools useful and applicable. They are:
(i) ELKI (for Environment for DeveLoping KDD-Applications Supported by Index-Structures)
(ii)Orange software
(iii) KNIME, the Konstanz Information Miner
(iv) RapidMiner
(v) Massive Online Analysis
I hope you will find them useful.
Kind regards
Olugbenga Oluwagbemi
Hi, extensions add functionality to RapidMiner, like text mining-, Weka-, parallel processing-, web mining-, and R- extensions.
Hi,
i am really with Pekka opinion. i have found all these software good as per perspective!
Regards
Muddsair
WordStat ? Here are some studies using WordStat in life scence: http://www.provalisresearch.com/Documents/SomeStudies.pdf
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