Characterization of microbial dark matter at scale with MetaSBT and taxonomy-aware Sequence Bloom Trees.

Unlabelled: Metagenomics has become a powerful tool for studying microbial communities, allowing researchers to investigate microbial diversity within complex environmental samples. Recent advances in sequencing technology have enabled the recovery of near-complete microbial genomes directly from metagenomic samples, also known as metagenome-assembled genomes (MAGs). However, accurately characterizing these genomes remains a significant challenge due to the presence of sequencing errors, incomplete assembly, and contamination.

Large-scale classification of metagenomic samples: a comparative analysis of classical machine learning techniques vs a novel brain-inspired hyperdimensional computing approach.

Classical machine learning techniques have revolutionized bioinformatics, enabling researchers to extract knowledge from complex biological data. However, these techniques often struggle with high-dimensional data, where the increasing number of features leads to decreased performance, also affecting models accuracy. To address this problem, we explore hyperdimensional computing (HDC), an emerging brain-inspired computational paradigm that leverages high-dimensional vectors and simple arithmetic operations to represent and manipulate complex patterns, as an alternative approach in the context of supervised machine learning.

How quantum computing can enhance biomarker discovery.

Biomarkers play a central role in medicine's gradual progress toward proactive, personalized precision diagnostics and interventions. However, finding biomarkers that provide very early indicators of a change in health status, for example, for multifactorial diseases, has been challenging. The discovery of such biomarkers stands to benefit significantly from advanced information processing and means to detect complex correlations, which quantum computing offers.

DICED (Database of Identified Cleavage Sites Endemic to Diseases States): A Searchable Web Interface for Terminomics/Degradomics.

Proteolysis is an irreversible posttranslational modification with immense biological impact. Owing to its high disease significance, there is growing interest in investigating proteolysis on the proteome scale, termed degradomics. We developed 'Database of Identified Cleavage sites Endemic to Disease states' (DICED; https://diced.

Feature selection with vector-symbolic architectures: a case study on microbial profiles of shotgun metagenomic samples of colorectal cancer.

Unlabelled: The continuously decreasing cost of next-generation sequencing has recently led to a significant increase in the number of microbiome-related studies, providing invaluable information for understanding host-microbiome interactions and their relation to diseases. A common approach in metagenomics consists of determining the composition of samples in terms of the amount and types of microbial species that populate them, with the goal of identifying microbes whose profiles are able to differentiate samples under different conditions with advanced feature selection techniques. Here, we propose a novel backward variable selection method based on the hyperdimensional computing (HDC) paradigm, which takes inspiration from how the human brain works in the classification of concepts by encoding features into vectors in a high-dimensional space.

Genomics to Notebook (g2nb): Extending the Electronic Notebook to Address the Challenges of Bioinformatics Analysis.

We present Genomics to Notebook (g2nb), an environment that combines the JupyterLab notebook system with widely-used bioinformatics platforms. The analyses and visualizations within those platforms are presented as cells in a notebook, making thousands of genomics methods available within the notebook metaphor and allowing notebooks to contain workflows utilizing multiple software packages on remote servers, all without the need for programming.

The Microbiology Galaxy Lab: A community-driven gateway to tools, workflows, and training for reproducible and FAIR analysis of microbial data.

Microbial research generates vast and complex data from diverse omics technologies, demanding innovative analytical solutions. The microGalaxy community addresses these needs with the Microbiology Lab, a user-friendly platform that integrates 290+ tool suites and 85+ curated workflows for microbial analyses, including taxonomic profiling, assembly, annotation, and functional analysis. Hosted on several public Galaxy servers (microbiology.

The next frontier in plastic surgery innovation: Quantum computing.

This work explores the transformative potential of quantum computing (QC) in plastic and reconstructive surgery, highlighting its ability to enhance predictive modeling, surgical planning, and intraoperative guidance. By leveraging QC's superior computational power, clinicians have the capacity to improve personalized treatment plans and optimize surgical outcomes. Despite the challenges of cost, technical limitations, and ethical considerations, the integration of QC into clinical practice and research promises significant advancements in patient care and surgical innovation.

Feature selection with vector-symbolic architectures: a case study on microbial profiles of shotgun metagenomic samples of colorectal cancer.

The continuingly decreasing cost of next-generation sequencing has recently led to a significant increase in the number of microbiome-related studies, providing invaluable information for understanding host-microbiome interactions and their relation to diseases. A common approach in metagenomics consists of determining the composition of samples in terms of the amount and types of microbial species that populate them, with the goal to identify microbes whose profiles are able to differentiate samples under different conditions with advanced feature selection techniques. Here we propose a novel backward variable selection method based on the hyperdimensional computing paradigm, which takes inspiration from how the human brain works in the classification of concepts by encoding features into vectors in a high-dimensional space.

How can quantum computing be applied in clinical trial design and optimization?

Clinical trials are necessary for assessing the safety and efficacy of treatments. However, trial timelines are severely delayed with minimal success due to a multitude of factors, including imperfect trial site selection, cohort recruitment challenges, lack of efficacy, absence of reliable biomarkers, etc. Each of these factors possesses a unique computational challenge, such as data management, trial simulations, statistical analyses, and trial optimization.

Generalized open-source workflows for atomistic molecular dynamics simulations of viral helicases.

Viral helicases are promising targets for the development of antiviral therapies. Given their vital function of unwinding double-stranded nucleic acids, inhibiting them blocks the viral replication cycle. Previous studies have elucidated key structural details of these helicases, including the location of substrate binding sites, flexible domains, and the discovery of potential inhibitors.

Homozygous EPRS1 missense variant causing hypomyelinating leukodystrophy-15 alters variant-distal mRNA mA site accessibility.

Hypomyelinating leukodystrophy (HLD) is an autosomal recessive disorder characterized by defective central nervous system myelination. Exome sequencing of two siblings with severe cognitive and motor impairment and progressive hypomyelination characteristic of HLD revealed homozygosity for a missense single-nucleotide variant (SNV) in EPRS1 (c.4444 C > A; p.

A Perspective on Protein Structure Prediction Using Quantum Computers.

Despite the recent advancements by deep learning methods such as AlphaFold2, protein structure prediction remains a challenging problem in biomedical research. With the rapid evolution of quantum computing, it is natural to ask whether quantum computers can offer some meaningful benefits for approaching this problem. Yet, identifying specific problem instances amenable to quantum advantage and estimating the quantum resources required are equally challenging tasks.

Sphingolipid biosynthesis is essential for metabolic rewiring during T17 cell differentiation.

T helper 17 (T17) cells are implicated in autoimmune diseases, and several metabolic processes are shown to be important for their development and function. In this study, we report an essential role for sphingolipids synthesized through the de novo pathway in T17 cell development. Deficiency of SPTLC1, a major subunit of serine palmitoyl transferase enzyme complex that catalyzes the first and rate-limiting step of de novo sphingolipid synthesis, impaired glycolysis in differentiating T17 cells by increasing intracellular reactive oxygen species (ROS) through enhancement of nicotinamide adenine dinucleotide phosphate oxidase 2 activity.

Contemporary Antiretroviral Therapy Dysregulates Iron Transport and Augments Mitochondrial Dysfunction in HIV-Infected Human Microglia and Neural-Lineage Cells.

HIV-associated cognitive dysfunction during combination antiretroviral therapy (cART) involves mitochondrial dysfunction, but the impact of contemporary cART on chronic metabolic changes in the brain and in latent HIV infection is unclear. We interrogated mitochondrial function in a human microglia (hμglia) cell line harboring inducible HIV provirus and in SH-SY5Y cells after exposure to individual antiretroviral drugs or cART, using the MitoStress assay. cART-induced changes in protein expression, reactive oxygen species (ROS) production, mitochondrial DNA copy number, and cellular iron were also explored.

Design and Synthesis of Thiazole Scaffold-Based Small Molecules as Anticancer Agents Targeting the Human Lactate Dehydrogenase A Enzyme.

A new series of thiazole central scaffold-based small molecules of LDHA inhibitors were designed using an approach. Molecular docking analysis of designed molecules with LDHA (PDB ID: 1I10) demonstrates that Ala 29, Val 30, Arg 98, Gln 99, Gly 96, and Thr 94 possessed strong interaction with the compounds. Compounds , , and showed good binding affinity (-8.

Phosphorylation-mediated regulation of the Bacillus anthracis phosphoglycerate mutase by the Ser/Thr protein kinase PrkC.

Bacillus anthracis Ser/Thr protein kinase PrkC is necessary for phenotypic memory and spore germination, and the loss of PrkC-dependent phosphorylation events affect the spore development. During sporulation, Bacillus sp. can store 3-Phosphoglycerate (3-PGA) that will be required at the onset of germination when ATP will be necessary.

CNV-ClinViewer: enhancing the clinical interpretation of large copy-number variants online.

Motivation: Pathogenic copy-number variants (CNVs) can cause a heterogeneous spectrum of rare and severe disorders. However, most CNVs are benign and are part of natural variation in human genomes. CNV pathogenicity classification, genotype-phenotype analyses, and therapeutic target identification are challenging and time-consuming tasks that require the integration and analysis of information from multiple scattered sources by experts.

Genomics to Notebook (g2nb): extending the electronic notebook to address the challenges of bioinformatics analysis.

We present Genomics to Notebook (g2nb), an environment that combines the JupyterLab notebook system with widely-used bioinformatics platforms. Galaxy, GenePattern, and the JavaScript versions of IGV and Cytoscape are currently available within g2nb. The analyses and visualizations within those platforms are presented as cells in a notebook, making thousands of genomics methods available within the notebook metaphor and allowing notebooks to contain workflows utilizing multiple software packages on remote servers, all without the need for programming.

Galaxy Training: A powerful framework for teaching!

There is an ongoing explosion of scientific datasets being generated, brought on by recent technological advances in many areas of the natural sciences. As a result, the life sciences have become increasingly computational in nature, and bioinformatics has taken on a central role in research studies. However, basic computational skills, data analysis, and stewardship are still rarely taught in life science educational programs, resulting in a skills gap in many of the researchers tasked with analysing these big datasets.

Evaluating homophily in networks via HONTO (HOmophily Network TOol): a case study of chromosomal interactions in human PPI networks.

Summary: It has been observed in different kinds of networks, such as social or biological ones, a typical behavior inspired by the general principle 'similarity breeds connections'. These networks are defined as homophilic as nodes belonging to the same class preferentially interact with each other. In this work, we present HONTO (HOmophily Network TOol), a user-friendly open-source Python3 package designed to evaluate and analyze homophily in complex networks.

Analysis of nested alternate open reading frames and their encoded proteins.

Transcriptional and post-transcriptional mechanisms diversify the proteome beyond gene number, while maintaining a sequence relationship between original and altered proteins. A new mechanism breaks this paradigm, generating novel proteins by translating alternative open reading frames (Alt-ORFs) within canonical host mRNAs. Uniquely, 'alt-proteins' lack sequence homology with host ORF-derived proteins.

Delivery of ceramide phosphoethanolamine lipids to the cleavage furrow through the endocytic pathway is essential for male meiotic cytokinesis.

Cell division, wherein 1 cell divides into 2 daughter cells, is fundamental to all living organisms. Cytokinesis, the final step in cell division, begins with the formation of an actomyosin contractile ring, positioned midway between the segregated chromosomes. Constriction of the ring with concomitant membrane deposition in a specified spatiotemporal manner generates a cleavage furrow that physically separates the cytoplasm.

Expanding the Galaxy's reference data.

Summary: Properly and effectively managing reference datasets is an important task for many bioinformatics analyses. Refgenie is a reference asset management system that allows users to easily organize, retrieve and share such datasets. Here, we describe the integration of refgenie into the Galaxy platform.