In recent years, scientists have dealt with a tidal wave of data arising from new technologies for sequencing data and obtaining three-dimensional structures of macromolecules. This demand for more computing power allowed an evolution of data processing technologies, ranging from using CPUs with increasingly miniaturized lithography to the adaptation of graphic cards for data analysis.
As a result, we live in a new era: the age of data science. It is an age in which data analysis is in high demand but also supported by more powerful hardware and technologies for sharing and processing data in real-time. Hence, software developers have been motivated to provide more creative technological solutions to harvest knowledge in life sciences, such as new methods, algorithms, and software tools.
In this context, software production is essential to novel discoveries in the fields of science. However, the newly produced software must be publicly available or open-source to allow other developers to benefit. User-friendly and easy-to-access graphical interfaces are also welcome, sometimes considered essential for most users, as well as comprehensive documentation and availability of tutorials. Additionally, artificial intelligence and machine learning approaches have become a differential to lead discoveries and find new paths. Thus, describing how these methodologies are applied is fundamental for reproducibility and replicability.
Research groups sometimes treat software production as a trivial task. However, these tools can play a key role in research. Recently, the scientific community has realized the importance of sharing computing strategies, methods, algorithms, and source codes of software tools.
Our goal is to provide a special issue for researchers and general software developers to disclose and share their methods, algorithms, and tools with the bioinformatics and computational biology community.
We hope the studies presented here could give insights and inspiration for developing new tools and lead to new scientific discoveries.
We are interested in papers describing new algorithms, methods, and tools for diverse fields, from bioinformatics to computational biology. Our scope includes novel algorithms, research pipelines, biological databases, and computational tools, including command-line scripts, graphical interfaces, and web applications. Additionally, we are open to submissions of previously published tool updates and new implementations or perspectives on the uses of these tools.
In recent years, scientists have dealt with a tidal wave of data arising from new technologies for sequencing data and obtaining three-dimensional structures of macromolecules. This demand for more computing power allowed an evolution of data processing technologies, ranging from using CPUs with increasingly miniaturized lithography to the adaptation of graphic cards for data analysis.
As a result, we live in a new era: the age of data science. It is an age in which data analysis is in high demand but also supported by more powerful hardware and technologies for sharing and processing data in real-time. Hence, software developers have been motivated to provide more creative technological solutions to harvest knowledge in life sciences, such as new methods, algorithms, and software tools.
In this context, software production is essential to novel discoveries in the fields of science. However, the newly produced software must be publicly available or open-source to allow other developers to benefit. User-friendly and easy-to-access graphical interfaces are also welcome, sometimes considered essential for most users, as well as comprehensive documentation and availability of tutorials. Additionally, artificial intelligence and machine learning approaches have become a differential to lead discoveries and find new paths. Thus, describing how these methodologies are applied is fundamental for reproducibility and replicability.
Research groups sometimes treat software production as a trivial task. However, these tools can play a key role in research. Recently, the scientific community has realized the importance of sharing computing strategies, methods, algorithms, and source codes of software tools.
Our goal is to provide a special issue for researchers and general software developers to disclose and share their methods, algorithms, and tools with the bioinformatics and computational biology community.
We hope the studies presented here could give insights and inspiration for developing new tools and lead to new scientific discoveries.
We are interested in papers describing new algorithms, methods, and tools for diverse fields, from bioinformatics to computational biology. Our scope includes novel algorithms, research pipelines, biological databases, and computational tools, including command-line scripts, graphical interfaces, and web applications. Additionally, we are open to submissions of previously published tool updates and new implementations or perspectives on the uses of these tools.