Robert Edgar's path to bioinformatics is quite different from that of most scientists in the field. His career started with a Physics Ph.D. in Particle Physics in 1982 from the University College in London. He then went on to create the company Parity Software that produced award winning software development tools for computer telephony applications. Dr. Edgar sold the company to Intel in 1999.
He then founded a new company drive5.com where he works as an independent scientist mostly developing computational biology and bioinformatics tools. The company' software resume is nothing short of astounding. It consist of a large number of simple, well documented, high performance tools among them the sequence search and clustering toolset of USearch, and the multiple sequence aligner MUSCLE. Overall these tools are a mainstain of modern bioinformatics and have been cited over ten thousand of times. Notably, and unlike the vast majority of bioinformatics applications, the tools developed by Dr. Edgar also run on Windows (reading his answers below we now know why).
What hardware do you use?
What is your text editor?
Microsoft Visual C++.
What software do you use for your work?
Microsoft Visual C++, Linux, Cygwin. The Microsoft C++ environment is far superior to any other C++ environment as far as I'm concerned; it's the main reason I do most of my work on Windows -- otherwise, I'd stick to Linux.
What do you use to create plots and charts?
Excel or my own home-grown code to generate SVG.
What do you consider the best language to do bioinformatics with?
There is no one best language. C/C++ is often the best for core algorithm development because speed is important for large datasets and/or compute-intensive code; assembler might be even better for optimizing inner loops. Scripting languages like bash, perl or python are good for creating analysis pipelines based on core algorithms like database search and clustering. Often, bioinformatician-hours are a critical resource, in which case it's whatever language you can use to solve a problem (correctly) with the least effort.
What bioinformatics tools/software do not get enough recognition?
Mine :-) Just kidding actually, I've been very fortunate in that regard.
See all post in this series https://www.biostars.org/t/uses-this/
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