Related papers: A how-to guide for code-sharing in biology
The broad sharing of research data is widely viewed as of critical importance for the speed, quality, accessibility, and integrity of science. Despite increasing efforts to encourage data sharing, both the quality of shared data, and the…
Scientific software often presents very particular requirements regarding usability, which is often completely overlooked in this setting. As computational science has emerged as its own discipline, distinct from theoretical and…
Computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results, however computational science lags behind. In the best case, authors may provide their source code as a…
The extent to which the benefits of science can be fully realized depends critically upon the quality of the connection between researchers themselves and between researchers and members of the public. We believe that it is now possible to…
Scientific software-defined as computer programs, scripts, or code used in scientific research, data analysis, modeling, or simulation-has become central to modern research. However, there is limited research on the readability and…
Biological science produces large amounts of data in a variety of formats, which necessitates the use of computational tools to process, integrate, analyse, and glean insights from the data. Researchers who use computational biology tools…
Biology-derived algorithms are an important part of computational sciences, which are essential to many scientific disciplines and engineering applications. Many computational methods are derived from or based on the analogy to natural…
Software production research is quickly evolving on two parallel approaches: conventional and bio-inspired. The bio-inspired approaches are generally developed and presented as enhancements of the conventional ones. However the conventional…
Computational problems can be classified according to their algorithmic complexity, which is defined based on how the resources needed to solve the problem, e.g. the execution time, scale with the problem size. Many problems in…
Motivation: Bioinformatics is faced with a variety of problems that require human involvement. Tasks like genome annotation, image analysis, knowledge-base construction and protein structure determination all benefit from human input. In…
Scientific code is not production software. Scientific code participates in the evaluation of a scientific hypothesis. This imposes specific constraints on the code that are often overlooked in practice. We articulate, with a small example,…
With the growing reliance on artificial intelligence (AI) for many different applications, the sharing of code, data, and models is important to ensure the replicability and democratization of scientific knowledge. Many high-profile…
Science communication forms the bridge between computer science researchers and their target audience. Researchers who can effectively draw attention to their research findings and communicate them comprehensibly not only help their target…
Computing in the life sciences has undergone a transformative evolution, from early computational models in the 1950s to the applications of artificial intelligence (AI) and machine learning (ML) seen today. This paper highlights key…
The complexity of human biology and its intricate systems holds immense potential for advancing human health, disease treatment, and scientific discovery. However, traditional manual methods for studying biological interactions are often…
Network biology is an interdisciplinary field bridging computational and biological sciences that has proved pivotal in advancing the understanding of cellular functions and diseases across biological systems and scales. Although the field…
Modern technologies are enabling scientists to collect extraordinary amounts of complex and sophisticated data across a huge range of scales like never before. With this onslaught of data, we can allow the focal point to shift towards…
Since the advent of next-generation sequencing in the early 2000s, the volume of bioinformatics software tools and databases has exploded and continues to grow rapidly. Documenting this evolution on a global and time-dependent scale is a…
Those seeking to reproduce a computational experiment often need to manually look at the code to see how to build necessary libraries, configure parameters, find data, and invoke the experiment; it is not automatic. Automatic…
Over 15 years of teaching, advising students and coordinating scientific research activities and projects in computer science, we have observed the difficulties of students to write scientific papers to present the results of their research…