JASPAR 2024: 20th anniversary of the open-access database of transcription factor binding profiles.

JASPAR (https://jaspar.elixir.no/) is a widely-used open-access database presenting manually curated high-quality and non-redundant DNA-binding profiles for transcription factors (TFs) across taxa. In this 10th release and 20th-anniversary update, the CORE collection has expanded with 329 new profiles. We updated three existing profiles and provided orthogonal support for 72 profiles from the previous release's UNVALIDATED collection. Altogether, the JASPAR 2024 update provides a 20% increase in CORE profiles from the previous release. A trimming algorithm enhanced profiles by removing low information content flanking base pairs, which were likely uninformative (within the capacity of the PFM models) for TFBS predictions and modelling TF-DNA interactions. This release includes enhanced metadata, featuring a refined classification for plant TFs' structural DNA-binding domains. The new JASPAR collections prompt updates to the genomic tracks of predicted TF binding sites (TFBSs) in 8 organisms, with human and mouse tracks available as native tracks in the UCSC Genome browser. All data are available through the JASPAR web interface and programmatically through its API and the updated Bioconductor and pyJASPAR packages. Finally, a new TFBS extraction tool enables users to retrieve predicted JASPAR TFBSs intersecting their genomic regions of interest.

Improving bioinformatics software quality through teamwork.

Since high-throughput techniques became a staple in biological science laboratories, computational algorithms, and scientific software have boomed. However, the development of bioinformatics software usually lacks software development quality standards. The resulting software code is hard to test, reuse, and maintain. We believe that the root of inefficiency in implementing the best software development practices in academic settings is the individualistic approach, which has traditionally been the norm for recognizing scientific achievements and, by extension, for developing specialized software. Software development is a collective effort in most software-heavy endeavors. Indeed, the literature suggests teamwork directly impacts code quality through knowledge sharing, collective software development, and established coding standards. In our computational biology research groups, we sustainably involve all group members in learning, sharing, and discussing software development while maintaining the personal ownership of research projects and related software products. We found that group members involved in this endeavor improved their coding skills, became more efficient bioinformaticians, and obtained detailed knowledge about their peers' work, triggering new collaborative projects. We strongly advocate for improving software development culture within bioinformatics through collective effort in computational biology groups or institutes with three or more bioinformaticians.

A new tool for the quantitative analysis of dendritic filopodial motility.

Dendritic filopodia are tiny and highly motile protrusions formed along the dendrites of neurons. During the search for future presynaptic partners, their shape and size change dynamically, with a direct impact on the formation, stabilization and maintenance of synaptic connections both in vivo and in vitro. In order to reveal molecular players regulating synapse formation, quantitative analysis of dendritic filopodia motility is needed. Defining the length or the tips of these protrusions manually, however, is time consuming, limiting the extent of studies as well as their statistical power. Additionally, area detection based on defining a single intensity threshold can lead to significant errors throughout the image series, as these small structures often have low contrast in fluorescent images. To overcome these problems, the open access Dendritic Filopodia Motility Analyzer, a semi-automated ImageJ/Fiji plugin was created. Our method calculates the displacement of the centre of mass (CoM) within a selected region based on the weighted intensity values of structure forming pixels, selected by upper and lower intensity thresholds. Using synthetic and real biological samples, we prove that the displacement of the weighted CoM reliably characterizes the motility of dendritic protrusions. Additionally, guidelines to define optimal parameters of live cell recordings from dendritic protrusions are provided. © 2014 International Society for Advancement of Cytometry.

iFISH is a publically available resource enabling versatile DNA FISH to study genome architecture.

DNA fluorescence in situ hybridization (DNA FISH) is a powerful method to study chromosomal organization in single cells. At present, there is a lack of free resources of DNA FISH probes and probe design tools which can be readily applied. Here, we describe iFISH, an open-source repository currently comprising 380 DNA FISH probes targeting multiple loci on the human autosomes and chromosome X, as well as a genome-wide database of optimally designed oligonucleotides and a freely accessible web interface ( http://ifish4u.org ) that can be used to design DNA FISH probes. We individually validate 153 probes and take advantage of our probe repository to quantify the extent of intermingling between multiple heterologous chromosome pairs, showing a much higher extent of intermingling in human embryonic stem cells compared to fibroblasts. In conclusion, iFISH is a versatile and expandable resource, which can greatly facilitate the use of DNA FISH in research and diagnostics.