Community-wide collaboration is a must to reinstall trust in bioinformatics solutions and biomedical interpretation

Abstract

Science has become a highly competitive undertaking concerning, for example, resources, positions, students, and publications. At the same time, the number of journals presenting scientific findings skyrockets while the knowledge increase per manuscript seems to be diminishing. Science has also become ever more dependent on computational analyses. For example, virtually all biomedical applications involve computational data analysis. The science community develops many computational tools, and there are numerous alternatives for many computational tasks. The same is true for workflow management systems, leading to a tremendous duplication of efforts. Software quality is often of low concern, and typically, a small dataset is used as a proof of principle to support rapid publication. Installation and usage of such tools are complicated, so virtual machine images, containers, and package managers are employed more frequently. These simplify installation and ease of use but do not solve the software quality issue and duplication of effort. We believe that a community-wide collaboration is needed to (a) ensure software quality, (b) increase reuse of code, (c) force proper software review, (c) increase testing, and (d) make interoperability more seamless. Such a science software ecosystem will overcome current issues and increase trust in current data analyses.

BGRS: bioinformatics of genome regulation and data integration

“…Integration of the bioinformatics resources and databases, standardization of data exchange became separate bioinformatics field [ 9 , 10 ]. Contemporary machine learning and Big Data analysis methods serve to solve the same problems of gene expression regulation in much larger scale [ 4 , 11 , 12 ].…”

“…To summarize and overview current trends note that main focus of the BGRS\SB-2022 conference was on the analysis of gene expression regulation in a genome on systems level, such as gene networks and systems biology models [ 5 ]. The necessity of community-wide collaboration is important for bioinformatics, as it was underlined in [ 11 ]. Linking of the metadata from the databases became a trend in integrative bioinformatics [ 40 , 41 ].…”