scholarly journals Ruby vs. Perl – the Languages of Bioinformatics

2013 ◽  
Vol 35 (1) ◽  
pp. 143-155
Author(s):  
Maciej Goliński ◽  
Agnieszka Kitlas Golińska
Keyword(s):  
Programming Languages ◽  
Programming Language ◽  
Protein Sequences ◽  
Nucleotide Sequences ◽  
Regular Expressions ◽  
Fasta File ◽  
Efficient Tool ◽  
Specific Nucleotide

Abstract Ruby and Perl are programming languages used in many fields. In this paper we would like to present their usefulness with regard to basic bioinformatic problems. We concentrate on a comparison of widely used Perl and relatively rarely used Ruby to show that Ruby can be a very efficient tool in bioinformatics. Both Perl and Ruby have a built-in regular expressions (or regexp) engine, which is essential in solving many problems in bioinformatics. We present some selected examples: printing the file content, removing comments from a FASTA file, using hashes, printing nucleotides included in a sequence, searching for a specific nucleotide in sequence and translating nucleotide sequences into protein sequences obtained in GenBank format. It is our belief that Ruby’s popularity will rise because of its simple syntax and the richness of its methods. Programs in Ruby are very easy to read and therefore easier to maintain and debug, which are the most important characteristics for a programming language.

PERANGKAT LUNAK KOMPUTER

2020 ◽  
Author(s):  
Cut Nabilah Damni
Keyword(s):  
Programming Languages ◽  
Programming Language ◽  
Operating Systems ◽  
Source Code ◽  
Computer Software ◽  
Computer Programs ◽  
Application Systems ◽  
Executable Programs

AbstrakSoftware komputer atau perangkat lunak komputer merupakan kumpulan instruksi (program atau prosedur) untuk dapat melaksanakan pekerjaan secara otomatis dengan cara mengolah atau memproses kumpulan intruksi (data) yang diberikan. (Yahfizham, 2019 : 19) Sebagian besar dari software komputer dibuat oleh (programmer) dengan menggunakan bahasa pemprograman. Orang yang membuat bahasa pemprograman menuliskan perintah dalam bahasa pemprograman seperti layaknya bahasa yang digunakan oleh orang pada umumnya dalam melakukan perbincangan. Perintah-perintah tersebut dinamakan (source code). Program komputer lainnya dinamakan (compiler) yang digunakan pada (source code) dan kemudian mengubah perintah tersebut kedalam bahasa yang dimengerti oleh komputer lalu hasilnya dinamakan program executable (EXE). Pada dasarnya, komputer selalu memiliki perangkat lunak komputer atau software yang terdiri dari sistem operasi, sistem aplikasi dan bahasa pemograman.AbstractComputer software or computer software is a collection of instructions (programs or procedures) to be able to carry out work automatically by processing or processing the collection of instructions (data) provided. (Yahfizham, 2019: 19) Most of the computer software is made by (programmers) using the programming language. People who make programming languages write commands in the programming language like the language used by people in general in conducting conversation. The commands are called (source code). Other computer programs called (compilers) are used in (source code) and then change the command into a language understood by the computer and the results are called executable programs (EXE). Basically, computers always have computer software or software consisting of operating systems, application systems and programming languages.

An Efficient Tool for Searching Maximal and Super Maximal Repeats in Large DNA/Protein Sequences via Induced-Enhanced Suffix Array

2019 ◽  
Vol 12 (2) ◽  
pp. 128-134
Author(s):  
Sanjeev Kumar ◽  
Suneeta Agarwal ◽  
Ranvijay
Keyword(s):  
Protein Sequences ◽  
Input Sequence ◽  
Suffix Array ◽  
Secondary Memory ◽  
Time And Space ◽  
Efficient Tool ◽  
Frequency Distributions ◽  
Alignment Algorithms ◽  
Common Prefix ◽  
Art Works

Background: DNA and Protein sequences of an organism contain a variety of repeated structures of various types. These repeated structures play an important role in Molecular biology as they are related to genetic backgrounds of inherited diseases. They also serve as a marker for DNA mapping and DNA fingerprinting. Efficient searching of maximal and super maximal repeats in DNA/Protein sequences can lead to many other applications in the area of genomics. Moreover, these repeats can also be used for identification of critical diseases by finding the similarity between frequency distributions of repeats in viruses and genomes (without using alignment algorithms). Objective: The study aims to develop an efficient tool for searching maximal and super maximal repeats in large DNA/Protein sequences. Methods: The proposed tool uses a newly introduced data structure Induced Enhanced Suffix Array (IESA). IESA is an extension of enhanced suffix array. It uses induced suffix array instead of classical suffix array. IESA consists of Induced Suffix Array (ISA) and an additional array-Longest Common Prefix (LCP) array. ISA is an array of all sorted suffixes of the input sequence while LCP array stores the lengths of the longest common prefixes between all pairs of consecutive suffixes in an induced suffix array. IESA is known to be efficient w.r.t. both time and space. It facilitates the use of secondary memory for constructing the large suffix-array. Results: An open source standalone tool named MSR-IESA for searching maximal and super maximal repeats in DNA/Protein sequences is provided at https://github.com/sanjeevalg/MSRIESA. Experimental results show that the proposed algorithm outperforms other state of the art works w.r.t. to both time and space. Conclusion: The proposed tool MSR-IESA is remarkably efficient for the analysis of DNA/Protein sequences, having maximal and super maximal repeats of any length. It can be used for identification of well-known diseases.

SSMBS: a web server to locate sequentially separated motifs in biological sequences

2009 ◽  
Vol 43 (1) ◽  
pp. 203-205 ◽  
Author(s):  
Chetan Kumar ◽  
K. Sekar
Keyword(s):  
Amino Acids ◽  
Web Server ◽  
Nucleotide Sequences ◽  
Regular Expressions ◽  
Biological Sequences ◽  
Sequence Motifs ◽  
Specific Order ◽  
The Web

The identification of sequence (amino acids or nucleotides) motifs in a particular order in biological sequences has proved to be of interest. This paper describes a computing server,SSMBS, which can locate and display the occurrences of user-defined biologically important sequence motifs (a maximum of five) present in a specific order in protein and nucleotide sequences. While the server can efficiently locate motifs specified using regular expressions, it can also find occurrences of long and complex motifs. The computation is carried out by an algorithm developed using the concepts of quantifiers in regular expressions. The web server is available to users around the clock at http://dicsoft1.physics.iisc.ernet.in/ssmbs/.

scholarly journals Techniques for the verification of minimal phylogenetic trees illustrated with ten mammalian haemoglobin sequences

1980 ◽  
Vol 187 (1) ◽  
pp. 65-74 ◽  
Author(s):  
D Penny ◽  
M D Hendy ◽  
L R Foulds
Keyword(s):  
Amino Acid ◽  
Phylogenetic Tree ◽  
Protein Sequence ◽  
Phylogenetic Trees ◽  
Sequence Data ◽  
Protein Sequences ◽  
Nucleotide Sequences ◽  
Amino Acid Sequences ◽  
Minimal Tree ◽  
Protein Sequence Data

We have recently reported a method to identify the shortest possible phylogenetic tree for a set of protein sequences [Foulds Hendy & Penny (1979) J. Mol. Evol. 13. 127–150; Foulds, Penny & Hendy (1979) J. Mol. Evol. 13, 151–166]. The present paper discusses issues that arise during the construction of minimal phylogenetic trees from protein-sequence data. The conversion of the data from amino acid sequences into nucleotide sequences is shown to be advantageous. A new variation of a method for constructing a minimal tree is presented. Our previous methods have involved first constructing a tree and then either proving that it is minimal or transforming it into a minimal tree. The approach presented in the present paper progressively builds up a tree, taxon by taxon. We illustrate this approach by using it to construct a minimal tree for ten mammalian haemoglobin alpha-chain sequences. Finally we define a measure of the complexity of the data and illustrate a method to derive a directed phylogenetic tree from the minimal tree.

scholarly journals Hybrid Java: The creation of a Hybrid Programming Environment

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Mark Noone ◽  
Aidan Mooney ◽  
Keith Nolan
Keyword(s):  
Programming Languages ◽  
Programming Language ◽  
Visual Programming ◽  
First Year ◽  
Programming Environment ◽  
Programming Environments ◽  
Hybrid Programming ◽  
Java Language ◽  
The Creation ◽  
Visual Programming Language

This article details the creation of a hybrid computer programming environment combining the power of the text-based Java language with the visual features of the Snap! language. It has been well documented that there exists a gap in the education of computing students in their mid-to-late teenage years, where perhaps visual programming languages are no longer suitable and textual programming languages may involve too steep of a learning curve. There is an increasing need for programming environments that combine the benefits of both languages into one. Snap! is a visual programming language which employs “blocks” to allow users to build programs, similar to the functionality offered by Scratch. One added benefit of Snap! is that it offers the ability to create one’s own blocks and extend the functionality of those blocks to create more complex and powerful programs. This will be utilised to create the Hybrid Java environment. The development of this tool will be detailed in the article, along with the motivation and use cases for it. Initial testing conducted will be discussed including one phase that gathered feedback from a pool of 174 first year Computer Science students. These participants were given instructions to work with the hybrid programming language and evaluate their experience of using it. The analysis of the findings along with future improvements to the language will also be presented.

scholarly journals Learners Programming Language a Helping System for Introductory Programming Courses

2016 ◽  
Vol 35 (3) ◽  
pp. 347-358
Author(s):  
Muhammad Shumail Naveed ◽  
Muhammad Sarim ◽  
Kamran Ahsan
Keyword(s):  
Programming Languages ◽  
Programming Language ◽  
Retention Rate ◽  
Introductory Programming ◽  
Source Program ◽  
Definition Of ◽  
High Level ◽  
Novice Students ◽  
Introductory Programming Courses ◽  
Programming Courses

Programming is the core of computer science and due to this momentousness a special care is taken in designing the curriculum of programming courses. A substantial work has been conducted on the definition of programming courses, yet the introductory programming courses are still facing high attrition, low retention and lack of motivation. This paper introduced a tiny pre-programming language called LPL (Learners Programming Language) as a ZPL (Zeroth Programming Language) to illuminate novice students about elementary concepts of introductory programming before introducing the first imperative programming course. The overall objective and design philosophy of LPL is based on a hypothesis that the soft introduction of a simple and paradigm specific textual programming can increase the motivation level of novice students and reduce the congenital complexities and hardness of the first programming course and eventually improve the retention rate and may be fruitful in reducing the dropout/failure level. LPL also generates the equivalent high level programs from user source program and eventually very fruitful in understanding the syntax of introductory programming languages. To overcome the inherent complexities of unusual and rigid syntax of introductory programming languages, the LPL provide elementary programming concepts in the form of algorithmic and plain natural language based computational statements. The initial results obtained after the introduction of LPL are very encouraging in motivating novice students and improving the retention rate.

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