Investments in AI for drug discovery are surging. Big Pharmas are throwing big bucks. Sanofi signed a 300 Million dollars deal with the…
The best things and stuff of 2017
Great blog posts read
- What’s next? – A wonderful post by Graydon Hoare where he explores what he sees as the direction that compiled languages will/should take in the coming years.
- Data Classes for Java – Brian Goetz runs through some design considerations for data classes in Java. The post highlights the stunning complexities around adding new features to Java. A very good example of a sorely-lacking genre of posting, namely design-thinking style posts.
- AlphaGo Zero: Learning from scratch – The AlphaGo program is generalized to a program that can teach itself game strategies and tactics through self-play.
- The languages which almost became CSS – A fascinating look at some of the languages around at the birth of CSS that might’ve served the same purpose instead.
- Writing an OS in Rust – A nice introduction to OSDev in Rust. I’ve been further exploring Redox OS also and have learned a lot about the Ruut/OSDev possibilities.
- The most beautiful program ever written – Will Byrd talks about the half-page LISP interpreter and its stunning beauty. Best talk of 2017 IMO. I found it inspirational even.
- The complete history of the IBM PC, pt. 1 – A very detailed account of the birth of the IBM PC.
- An English Guide to Sanuki Udon – If you’re a fan of Japanese food then this is a must read.
- Why Kotlin Is Better Than Whatever Dumb Language You’re Using – Very typical Steve Yegge post with his normal wit mixed with his flavor of bombastic.
- Mystery Science Theater 3000: The Definitive Oral History of a TV Masterpiece – A history of the greatest television show ever created.
- How to see the future – Warren Ellis talks about how to see the future, even when it’s already occurred. Inspiring.
Bioinformatics /ˌbaɪ.oʊˌɪnfərˈmætɪks/ ( listen) is an interdisciplinary field that develops methods and software tools for understanding biological data. As an interdisciplinary field of science, bioinformatics combines Computer Science, Biology, Mathematics, and Engineering to analyze and interpret biological data. Bioinformatics has been used for in silico analyses of biological queries using mathematical and statistical techniques.
Bioinformatics is both an umbrella term for the body of biological studies that use computer programming as part of their methodology, as well as a reference to specific analysis “pipelines” that are repeatedly used, particularly in the field of genomics. Common uses of bioinformatics include the identification of candidate genes and single nucleotide polymorphisms (SNPs). Often, such identification is made with the aim of better understanding the genetic basis of disease, unique adaptations, desirable properties (esp. in agricultural species), or differences between populations. In a less formal way, bioinformatics also tries to understand the organisational principles within nucleic acid and protein sequences, called proteomics.
Source: Bioinformatics – Wikiwand
As a little boy in Oxford, I was encouraged to worship the mind. I and my friends, often sons of professors, were being drilled in French and Latin and Greek before we turned seven, and not long afterwards were to be found wrestling with Occam’s razors and Pythagorean theorems. We learned how to write with spurious fluency on every aspect of Plato or King Lear, and the less we knew, the more commandingly we could write. The mind became an instrument we could deploy as sword, shield and moat; on its own terms – and they were the only terms we were taught to honour – it was impossible to defeat.