The blockchain cannot be described just as a revolution. It is a tsunami-like phenomenon, slowly advancing and gradually enveloping everything along its way by the force of its progression. - William Mougayar I think the whole narrative of blockchain without bitcoin will amount to very little. - Fred Ehrsam We want a language that’s open source, with a liberal license. We want the speed of C with the dynamism of Ruby. We want a language that’s homoiconic, with true macros like Lisp, but with obvious, familiar mathematical notation like Matlab. We want something as usable for general programming as Python, as easy for statistics as R, as natural for string processing as Perl, as powerful for linear algebra as Matlab, as good at gluing programs together as the shell. Something that is dirt simple to learn, yet keeps the most serious hackers happy. We want it interactive and we want it compiled. Why We Created Julia - Jeff Bezanson, Stefan Karpinski, Viral Shah, ...
Recently, we wanted to remove low quality and duplicate reads from .bam alignment files to make viewing them in the UCSC genome browser easier. Our definition of low quality is stringent. We consider a read as low quality if it has any base with a base call quality below 30. To filter low quality reads and duplicates, we use a combination of samtools and the python PySam library. samtools has an option to remove PCR and optical duplicates and we use PySam to filter low quality reads. PySam allows us to read and write bam files. To filter out low quality reads, we loop through the input bam file, check the read quality to see if any base call falls below 30. If all of the base call qualities are 30 or above, we write the read to a new file. Here's one way to filter: def FilterReads(chrom, in_file, out_file): def read_ok(read): """ read_ok - reject reads with a low quality (be...
Genetic Algorithms are a class of global optimizers that are particularly effective in cases where the objective function is a black box or is discrete and derivatives can't easily be calculated.. They are also effective in cases where the objective function is smooth or convex. It's just that in these cases, the availability of derivatives often makes other methods such as gradient descent faster. Sometimes, the target function might have competing objectives, for example designing a treatment plan that maximizes efficacy while minimizing adverse side-effects. In cases like this, we often want not a local or even global optimal solution, but also what are the tradeoffs among the goals. In other words, there’s no single “best” solution. Instead, you want the Pareto set : solutions where you can’t improve any objective without worsening another. The Pareto set or Pareto front consists of the possible solutions that are not dominated by any other solution. What we mean by...
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