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The improvement and decreasing costs of third‐generation sequencing technologies has widened the scope of biological questions researchers can address with de novo genome assemblies. With the increasing number of reference genomes, validating their integrity with minimal overhead is vital for establishing confident results in their applications. Here, we present Klumpy, a tool for detecting and visualizing both misassembled regions in a genome assembly and genetic elements (e.g. genes) of interest in a set of sequences. By leveraging the initial raw reads in combination with their respective genome assembly, we illustrate Klumpy's utility by investigating antifreeze glycoprotein (afgp) loci across two icefishes, by searching for a reported absent gene in the northern snakehead fish, and by scanning the reference genomes of a mudskipper and bumblebee for misassembled regions. In the two former cases, we were able to provide support for the noncanonical placement of an afgp locus in the icefishes and locate the missing snakehead gene. Furthermore, our genome scans were able identify an unmappable locus in the mudskipper reference genome and identify a putative repetitive element shared among several species of bees. [ABSTRACT FROM AUTHOR]

This document is an editorial titled "Bioinformatics for modern neuroscience" published in the journal Frontiers in Computational Neuroscience. The editorial discusses the use of bioinformatics in neuroscience research, particularly in understanding the functioning of the nervous system. It highlights the advancements in computing power that have made bioinformatics more accessible to researchers. The editorial also summarizes several articles published in a research topic on bioinformatics for neuroscience, including topics such as analyzing transcriptomics data, bibliometric analysis of glioma research, personalized treatment for post-traumatic stress disorder (PTSD), protein misfolding in neurodegenerative diseases, and the role of the endocannabinoid system in epilepsy. The editorial concludes by emphasizing the importance of integrating in silico experiments with traditional lab-based research in neuroscience. [Extracted from the article]