Discovery of a drug target requires expertise from different arms of a cell metabolism lab. A typical cell metabolism lab has a core biology facility that performs wet lab experiments, separate metabolomics and genomics core facilities, and a bioinformatics group to aid the core facilities. This is a case study of one such lab where … Continue reading Polly: An Ecosystem that Enables Cell Metabolism Labs
With the advances in next-generation sequencing technologies over the past decade, genomics has gradually caught up to the big data giants – YouTube, Amazon, and Twitter to name a few – in terms of its requirement for data storage and computational needs. By 2025, the storage requirements for human DNA sequences alone is projected to … Continue reading Big Data driven drug-discovery
Introduction: In 1990, an ambitious project was launched in the USA to sequence the human DNA and identify, both functionally and structurally, genes that makeup the whole genome. It was called the Human Genome Project (HGP). A few years later, another ambitious project was launched to study the abnormal human DNA – The Cancer Genome … Continue reading Story of a Gene: Making Sense of the Random Errors of Life
Image Source: quantica.com.co One of the key issues that data scientists face is keeping track of the results, and sharing the progress of the project among their colleagues. In data science, decisions are made based on results so just sharing a chunk of code makes no sense unless the results (graphs, tables, etc.) are stated. … Continue reading Knowledge Repo for Data Science
You may have probably read Boyd’s law of iteration. If you haven’t, already, have a look at it. In Roger’s words: “In analyzing complexity, fast iteration almost always produces better results than in-depth analysis.” This is especially true of exploratory work, where the goals are not well defined, and can possibly change with time. Boyd’s … Continue reading From Fighter Planes to Omics: Why Iterate?
Problem Statement Principal component analysis (PCA) is a fairly common statistical technique used to reduce the dimensions of data containing a large set of interrelated variables. Problems start to arise when the number of observations and variables are very large. At this point classical PCA techniques require sizeable memory and immense computational time. While working with … Continue reading Principal Component Analysis on Big data
After the blog by Susan Fowler and Indian Fowler, various articles came up about the lax laws against harassment in Indian startups, ‘bro-culture’ in startups or perhaps tech community in general. These things are not new, workplace harassment is still not tackled very well in Indian corporates, the tech community was never women-friendly, and these … Continue reading Breaking the Stereotype of Gender Biasness in Indian Tech Startups
by Kailash Yadav (firstname.lastname@example.org)
Point of contact: Raaisa (email@example.com)
Python has many great inbuilt packages that make solving system of ODEs a piece of cake. In this post I will explain how we can use Sympy, Scipy, Numpy and some other libraries to solve a system of ODEs.
by Raaisa (firstname.lastname@example.org)
PEP8 guidelines state ‘a code is read much more often than it is written’. Writing a clean code is as important as writing a working code and maintaining code cleanliness can get tough when ignored for long.