Efficient protein structure archiving using ProteStAr.

Motivation: The introduction of Deep Minds' Alpha Fold 2 enabled the prediction of protein structures at an unprecedented scale. AlphaFold Protein Structure Database and ESM Metagenomic Atlas contain hundreds of millions of structures stored in CIF and/or PDB formats. When compressed with a general-purpose utility like gzip, this translates to tens of terabytes of data, which hinders the effective use of predicted structures in large-scale analyses.

Towards the accurate alignment of over a million protein sequences: Current state of the art.

Large-scale genomics requires highly scalable and accurate multiple sequence alignment methods. Results collected over this last decade suggest accuracy loss when scaling up over a few thousand sequences. This issue has been actively addressed with a number of innovative algorithmic solutions that combine low-level hardware optimization with novel higher-level heuristics.

CoLoRd: compressing long reads.

The cost of maintaining exabytes of data produced by sequencing experiments every year has become a major issue in today's genomic research. In spite of the increasing popularity of third-generation sequencing, the existing algorithms for compressing long reads exhibit a minor advantage over the general-purpose gzip. We present CoLoRd, an algorithm able to reduce the size of third-generation sequencing data by an order of magnitude without affecting the accuracy of downstream analyses.

PHIST: fast and accurate prediction of prokaryotic hosts from metagenomic viral sequences.

Summary: Phage-Host Interaction Search Tool (PHIST) predicts prokaryotic hosts of viruses based on exact matches between viral and host genomes. It improves host prediction accuracy at species level over current alignment-based tools (on average by 3 percentage points) as well as alignment-free and CRISPR-based tools (by 14-20 percentage points). PHIST is also two orders of magnitude faster than alignment-based tools making it suitable for metagenomics studies.

Whisper: read sorting allows robust mapping of DNA sequencing data.

Motivation: Mapping reads to a reference genome is often the first step in a sequencing data analysis pipeline. The reduction of sequencing costs implies a need for algorithms able to process increasing amounts of generated data in reasonable time.

Results: We present Whisper, an accurate and high-performant mapping tool, based on the idea of sorting reads and then mapping them against suffix arrays for the reference genome and its reverse complement.

Kmer-db: instant evolutionary distance estimation.

Summary: Kmer-db is a new tool for estimating evolutionary relationship on the basis of k-mers extracted from genomes or sequencing reads. Thanks to an efficient data structure and parallel implementation, our software estimates distances between 40 715 pathogens in <7 min (on a modern workstation), 26 times faster than Mash, its main competitor.

Availability And Implementation: https://github.

Learning rule sets from survival data.

Background: Survival analysis is an important element of reasoning from data. Applied in a number of fields, it has become particularly useful in medicine to estimate the survival rate of patients on the basis of their condition, examination results, and undergoing treatment. The recent developments in the next generation sequencing open new opportunities in survival study as they allow vast amount of genome-, transcriptome-, and proteome-related features to be investigated.

QuickProbs 2: Towards rapid construction of high-quality alignments of large protein families.

The ever-increasing size of sequence databases caused by the development of high throughput sequencing, poses to multiple alignment algorithms one of the greatest challenges yet. As we show, well-established techniques employed for increasing alignment quality, i.e.

FAMSA: Fast and accurate multiple sequence alignment of huge protein families.

Rapid development of modern sequencing platforms has contributed to the unprecedented growth of protein families databases. The abundance of sets containing hundreds of thousands of sequences is a formidable challenge for multiple sequence alignment algorithms. The article introduces FAMSA, a new progressive algorithm designed for fast and accurate alignment of thousands of protein sequences.

QuickProbs--a fast multiple sequence alignment algorithm designed for graphics processors.

Multiple sequence alignment is a crucial task in a number of biological analyses like secondary structure prediction, domain searching, phylogeny, etc. MSAProbs is currently the most accurate alignment algorithm, but its effectiveness is obtained at the expense of computational time. In the paper we present QuickProbs, the variant of MSAProbs customised for graphics processors.

HuntMi: an efficient and taxon-specific approach in pre-miRNA identification.

Background: Machine learning techniques are known to be a powerful way of distinguishing microRNA hairpins from pseudo hairpins and have been applied in a number of recognised miRNA search tools. However, many current methods based on machine learning suffer from some drawbacks, including not addressing the class imbalance problem properly. It may lead to overlearning the majority class and/or incorrect assessment of classification performance.

ERISdb: a database of plant splice sites and splicing signals.

Splicing is one of the major contributors to observed spatiotemporal diversification of transcripts and proteins in metazoans. There are numerous factors that affect the process, but splice sites themselves along with the adjacent splicing signals are critical here. Unfortunately, there is still little known about splicing in plants and, consequently, further research in some fields of plant molecular biology will encounter difficulties.