Vijini Mallawaarachchi

Blog

Here are some of my blog articles on bioinformatics, data structures, algorithms, data science and other topics that interest me.

/ Bioinformatics, Genomics, Metagenomics

Marker Genes and Gene Prediction of Bacteria

When we think of the word marker, the first thing that comes to our minds is something that is used to indicate a place. For example, it can be your current location on Google Maps or it can be the place where you planted some seeds in your garden.

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/ Bioinformatics, Genomics

Assessing the Quality of Genome Assemblies using QUAST

The assembly algorithms that have been developed so far intend to provide better assemblies evaluated under different criteria. Hence, depending on the specific scenario the assembly process might produce better results if we use the most appropriate assembler.

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/ Binning, Bioinformatics, Data Science, Genomics, Metagenomics

Software Tools for Reference-free Binning of Metagenomes

We know that there are trillions of microbes in the environment surrounding us, even in our bodies. These microscopic communities have very diverse ecosystems and by studying their composition and behaviour we can learn a lot about them.

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/ Bioinformatics, Genomics, Metagenomics

Metagenomics — Who is there and what are they doing?

Did you know that your body houses about 100 trillion bacteria? Estimates show that a human has approximately a pound or two of bacteria living in his/her gut (stomach) [1] (Now don’t go and drink all the antibiotics you know, to kill those bacteria.

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/ Bioinformatics, Computer Science, Data Science, Workflow Management

Bioinformatics Workflow Management Systems: Introducing Unipro UGENE to model Bioinformatics Workflows

With the development of various methods to obtain data from living beings, there has been an explosion in biological data which is readily available to be used. However, such vast amounts of data will be of no use if there is no proper way to execute a series of steps to manipulate the data as we want, to output desired results.

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/ Algorithms, Bioinformatics, Computer Science, Data Science, Genomics

Molecular Phylogenetics using Bio.Phylo

Have you ever wondered how life formed from the primordial soup and evolved to the different life forms which can be seen at present? How did different species evolved from their ancestors and what relationships do they have with each other?

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/ Algorithms, Bioinformatics, Computer Science, Data Science, Genomics

Multiple Sequence Alignment using Clustal Omega and T-Coffee

Have you wondered how scientists identify regions of similarity in three or more biological sequences? As described in my previous article, Sequence alignment is a method of arranging sequences of DNA, RNA, or protein to identify regions of similarity.

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/ Bioinformatics, Data Science, Genomics

Pipeline Frameworks for Genomic Data

Yesterday I was returning home from university via the expressway and the oil refinery at Sapugaskanda caught my eye. The refinery towers operate while sending huge flames into the sky with smoke.

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/ Bioinformatics, Computer Science, Data Science, Genomics

Starting off in Bioinformatics — DNA Nucleotides and Strands

In my first article where I introduced bioinformatics, I have mentioned that we will be learning a lot about DNA, RNA and Protein sequences. Since I’m new to all these DNA/RNA jargon, I decided to learn about them first and then try out some coding problems.

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/ Bioinformatics, Computer Science, Data Science, Genomics

A Dummies’ Intro to Bioinformatics

The word Bioinformatics is making quite a turnaround in today’s world of Science. The word seems to be made up of two parts which are related to two different fields, biology and computer science.

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/ Data, Information Retrieval

Life without Search Engines – How would it be?

Whenever we find something that we do not know, or when we cannot find a solution to a problem, the first thing we do is search on Google. Google has become so close to our lives that it eventually has become a commonly used verb in the English language.

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/ Algorithms, Machine Learning

Introduction to Genetic Algorithms

A genetic algorithm is a search heuristic that is inspired by Charles Darwin’s theory of natural evolution. This algorithm reflects the process of natural selection where the fittest individuals are selected for reproduction in order to produce offspring of the next generation.

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/ Algorithm Analysis, Algorithms, Data Structures

Amortized Analysis – A basic introduction

In amortized analysis, we average the time needed to perform a sequence of data structure operations. By this method, we can show that the average cost of an operation is small, even if we have a single operation within the sequence which might be expensive.

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/ Data, Databases, Space

Outer Space Databases — Is it possible?

Have you ever imagined how it will be to have databases on different planets? How long will it take for queries to process and return results among databases on different planets?

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/ Algorithms, Data Structures

B Trees – All you need to know about deleting keys

B tree is a self-balancing search tree (the tree adjusts itself so that all the leaves are at the same depth) and contains multiple nodes which keep data in sorted order. Each node has 2 or more children, known as the branching factor and consists of multiple keys.

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