DNA Features Viewer: a sequence annotation formatting and plotting library for Python

AbstractMotivationWhile the Python programming language counts many Bioinformatics and Computational Biology libraries, none offers customizable sequence annotations visualizations with layout optimization.ResultsDNA Features Viewer is a sequence annotations plotting library which optimizes plot readability while letting users tailor other visual aspects (colors, labels, highlights, etc.) to their particular use case.AvailabilityOpen-source code and documentation are available on Github under the MIT licence (https://github.com/Edinburgh-Genome-Foundry/DnaFeaturesViewer)[email protected] informationattached.

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An Open Source Finance System for Stocks Backtesting Trade Strategies

International Journal of Open Source Software and Processes ◽

10.4018/ijossp.2021040104 ◽

2021 ◽

Vol 12 (2) ◽

pp. 52-65

Author(s):

Eviatar Rosenberg ◽

Dima Alberg

Keyword(s):

User Interface ◽

Open Source ◽

Programming Language ◽

Capital Market ◽

Historical Data ◽

Trading Strategies ◽

Market Volatility ◽

Finance System ◽

Python Programming Language ◽

Python Programming

A significant part of pension savings is in the capital market and exposed to market volatility. The COVID-19 pandemic crisis, like the previous crises, damaged the gains achieved in those funds. This paper presents a development of open-source finance system for stocks backtesting trade strategies. The development will be operated by the Python programming language and will implement application user interface. The system will import historical data of stocks from financial web and will produce charts for analysis of the trends in stocks price. Based on technical analysis, it will run trading strategies which will be defined by the user. The system will output the trade orders that should have been executed in retrospect and concluding charts to present the profit and loss that would occur to evaluate the performance of the strategy.

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ATLaS: Assistant Software for Life Scientists to Use in Calculations of Buffer Solutions

Tehnički glasnik ◽

10.31803/tg-20210326070107 ◽

2021 ◽

Vol 15 (4) ◽

pp. 541-545

Author(s):

Ugur Comlekcioglu ◽

Nazan Comlekcioglu

Keyword(s):

Programming Language ◽

Life Science ◽

Source Code ◽

Experimental Results ◽

Acid Base ◽

Buffer Solutions ◽

Python Programming Language ◽

Science Laboratories ◽

Executable File ◽

Python Programming

Many solutions such as percentage, molar and buffer solutions are used in all experiments conducted in life science laboratories. Although the preparation of the solutions is not difficult, miscalculations that can be made during intensive laboratory work negatively affect the experimental results. In order for the experiments to work correctly, the solutions must be prepared completely correctly. In this project, a software, ATLaS (Assistant Toolkit for Laboratory Solutions), has been developed to eliminate solution errors arising from calculations. Python programming language was used in the development of ATLaS. Tkinter and Pandas libraries were used in the program. ATLaS contains five main modules (1) Percent Solutions, (2) Molar Solutions, (3) Acid-Base Solutions, (4) Buffer Solutions and (5) Unit Converter. Main modules have sub-functions within themselves. With PyInstaller, the software was converted into a stand-alone executable file. The source code of ATLaS is available at https://github.com/cugur1978/ATLaS.

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scikit-image: Image processing in Python

10.7287/peerj.preprints.336v1 ◽

2014 ◽

Cited By ~ 2

Author(s):

Stéfan van der Walt ◽

Johannes L Schönberger ◽

Juan Nunez-Iglesias ◽

François Boulogne ◽

Joshua D Warner ◽

...

Keyword(s):

Image Processing ◽

Open Source ◽

Programming Language ◽

Real World ◽

Research Education ◽

Python Programming Language ◽

Image Library ◽

Industry Applications ◽

Python Programming ◽

World Image

scikit-image is an image processing library that implements algorithms and utilities for use in research, education and industry applications. It is released under the liberal "Modified BSD" open source license, provides a well-documented API in the Python programming language, and is developed by an active, international team of collaborators. In this paper we highlight the advantages of open source to achieve the goals of the scikit-image library, and we showcase several real-world image processing applications that use scikit-image.

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GlycanFormatConverter: a conversion tool for translating the complexities of glycans

Bioinformatics ◽

10.1093/bioinformatics/bty990 ◽

2018 ◽

Vol 35 (14) ◽

pp. 2434-2440 ◽

Cited By ~ 7

Author(s):

Shinichiro Tsuchiya ◽

Issaku Yamada ◽

Kiyoko F Aoki-Kinoshita

Keyword(s):

Open Source ◽

Source Code ◽

Supplementary Information ◽

Biological Processes ◽

Supplementary Data ◽

Unique Representation ◽

Open Source Tool ◽

Living Organisms ◽

Conversion Tool ◽

Complex Glycan

Abstract Motivation Glycans are biomolecules that take an important role in the biological processes of living organisms. They form diverse, complicated structures such as branched and cyclic forms. Web3 Unique Representation of Carbohydrate Structures (WURCS) was proposed as a new linear notation for uniquely representing glycans during the GlyTouCan project. WURCS defines rules for complex glycan structures that other text formats did not support, and so it is possible to represent a wide variety glycans. However, WURCS uses a complicated nomenclature, so it is not human-readable. Therefore, we aimed to support the interpretation of WURCS by converting WURCS to the most basic and widely used format IUPAC. Results In this study, we developed GlycanFormatConverter and succeeded in converting WURCS to the three kinds of IUPAC formats (IUPAC-Extended, IUPAC-Condensed and IUPAC-Short). Furthermore, we have implemented functionality to import IUPAC-Extended, KEGG Chemical Function (KCF) and LinearCode formats and to export WURCS. We have thoroughly tested our GlycanFormatConverter and were able to show that it was possible to convert all the glycans registered in the GlyTouCan repository, with exceptions owing only to the limitations of the original format. The source code for this conversion tool has been released as an open source tool. Availability and implementation https://github.com/glycoinfo/GlycanFormatConverter.git Supplementary information Supplementary data are available at Bioinformatics online.

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Phigaro: high-throughput prophage sequence annotation

Bioinformatics ◽

10.1093/bioinformatics/btaa250 ◽

2020 ◽

Vol 36 (12) ◽

pp. 3882-3884 ◽

Cited By ~ 2

Author(s):

Elizaveta V Starikova ◽

Polina O Tikhonova ◽

Nikita A Prianichnikov ◽

Chris M Rands ◽

Evgeny M Zdobnov ◽

...

Keyword(s):

Test Data ◽

High Throughput ◽

Source Code ◽

Supplementary Information ◽

Sequence Annotation ◽

Command Line ◽

Supplementary Data ◽

Genome Maps ◽

Transposon Insertion ◽

Prophage Sequence

Abstract Summary Phigaro is a standalone command-line application that is able to detect prophage regions taking raw genome and metagenome assemblies as an input. It also produces dynamic annotated ‘prophage genome maps’ and marks possible transposon insertion spots inside prophages. It is applicable for mining prophage regions from large metagenomic datasets. Availability and implementation Source code for Phigaro is freely available for download at https://github.com/bobeobibo/phigaro along with test data. The code is written in Python. Supplementary information Supplementary data are available at Bioinformatics online.

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scikit-image: Image processing in Python

10.7287/peerj.preprints.336v2 ◽

2014 ◽

Cited By ~ 2

Author(s):

Stéfan van der Walt ◽

Johannes L Schönberger ◽

Juan Nunez-Iglesias ◽

François Boulogne ◽

Joshua D Warner ◽

...

Keyword(s):

Image Processing ◽

Open Source ◽

Programming Language ◽

Real World ◽

Research Education ◽

Python Programming Language ◽

Image Library ◽

Industry Applications ◽

Python Programming ◽

World Image

scikit-image is an image processing library that implements algorithms and utilities for use in research, education and industry applications. It is released under the liberal "Modified BSD" open source license, provides a well-documented API in the Python programming language, and is developed by an active, international team of collaborators. In this paper we highlight the advantages of open source to achieve the goals of the scikit-image library, and we showcase several real-world image processing applications that use scikit-image.

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CNC Programming Software Design to Optimizing Batik Stamping Time

OPSI ◽

10.31315/opsi.v14i1.4700 ◽

2021 ◽

Vol 14 (1) ◽

pp. 21

Author(s):

Rian Prasetyo ◽

Ainur Komariah

Keyword(s):

Programming Language ◽

Design Process ◽

Software Design ◽

Source Code ◽

Python Programming Language ◽

Cnc Programming ◽

G Code ◽

Programming Software ◽

Python Programming ◽

Research Show

Batik is an original Indonesian heritage, that must be preserved and it is the mainstay for implementation of “Making Indonesia 4.0”. It was published many research about stamp batik manufacturing, but still have limitation of motive variation and slackly design process. This research aim to develop the way to making CNC program to be quickly, besides of high variation of batik motive. Source code in python programming language, was built for extension tool in inscape software. Extentension is used to create stamp point, depend on various motive size. Source code created in .py and .inx format will be save in “ekstensi” folder. Based on coordinate point of stamping in stamp batik, CNC program will be created, using “G-code tools” extension that was available in inscape software menubar. CNC programming used extension was built is measured about time of process and compared to manual CNC programming. CNC program that has been built then tested in CAMotics software. The results of this research show that CNC program could maked with this extension for various dimension od batik stamp and in 2, 4, 6, 8, 10, and 12 meters of cloth length. CNC programming with extension developed, can reduce time up to 96.05%.

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scikit-image: Image processing in Python

10.7287/peerj.preprints.336 ◽

2014 ◽

Cited By ~ 1

Author(s):

Stéfan van der Walt ◽

Johannes L Schönberger ◽

Juan Nunez-Iglesias ◽

François Boulogne ◽

Joshua D Warner ◽

...

Keyword(s):

Image Processing ◽

Open Source ◽

Programming Language ◽

Real World ◽

Research Education ◽

Python Programming Language ◽

Image Library ◽

Industry Applications ◽

Python Programming ◽

World Image

scikit-image is an image processing library that implements algorithms and utilities for use in research, education and industry applications. It is released under the liberal "Modified BSD" open source license, provides a well-documented API in the Python programming language, and is developed by an active, international team of collaborators. In this paper we highlight the advantages of open source to achieve the goals of the scikit-image library, and we showcase several real-world image processing applications that use scikit-image.

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A Python application to generate digital signals

Studia Universitatis Babeș-Bolyai Engineering ◽

10.24193/subbeng.2020.1.10 ◽

2020 ◽

Vol 65 (1) ◽

pp. 96-104

Author(s):

Tatian-Cristian Mălin

Keyword(s):

Numerical Simulation ◽

Programming Language ◽

Digital Signals ◽

Python Programming Language ◽

Python Programming

We introduce in this paper an application developed in the Python programming language that can be used to generate digital signals with known frequencies and amplitudes. These digital signals, since have known parameters, can be used to create benchmarks for test and numerical simulation.

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