MRGM: an enhanced catalog of mouse gut microbial genomes substantially broadening taxonomic and functional landscapes.

Mouse gut microbiome research is pivotal for understanding the human gut microbiome, providing insights into disease modeling, host-microbe interactions, and the dietary influence on the gut microbiome. To enhance the translational value of mouse gut microbiome studies, we need detailed and high-quality catalogs of mouse gut microbial genomes. We introduce the Mouse Reference Gut Microbiome (MRGM), a comprehensive catalog with 42,245 non-redundant mouse gut bacterial genomes across 1,524 species.

MRGM: An enhanced catalog of mouse gut microbial genomes substantially broadening taxonomic and functional landscapes.

Mouse gut microbiome research is pivotal for understanding the human gut microbiome, providing insights into disease modeling, host-microbe interactions, and the dietary influence on the gut microbiome. To enhance the translational value of mouse gut microbiome studies, we need detailed and high-quality catalogs of mouse gut microbial genomes. We introduce the Mouse Reference Gut Microbiome (MRGM), a comprehensive catalog with 42,245 non-redundant mouse gut bacterial genomes across 1,524 species.

COVID-GWAB: A Web-Based Prediction of COVID-19 Host Genes via Network Boosting of Genome-Wide Association Data.

Host genetics affect both the susceptibility and response to viral infection. Searching for host genes that contribute to COVID-19, the Host Genetics Initiative (HGI) was formed to investigate the genetic factors involved in COVID-19 via genome-wide association studies (GWAS). The GWAS suffer from limited statistical power and in general, only a few genes can pass the conventional significance thresholds.

Comparison of Postoperative Gastrointestinal Motility of Sugammadex and Neostigmine in Patients Undergoing Robotic Thyroidectomy: A Retrospective Study.

Postoperative bowel dysfunction poses difficulty to patients during their recovery from surgery, and reversal agents may affect bowel function. This study aimed to investigate and compare the effects of sugammadex and a neostigmine/glycopyrrolate combination on postoperative bowel movement in patients undergoing robotic thyroidectomy. The electronic medical records of 122 patients, who underwent robotic thyroidectomy between March 2018 and December 2020, were retrospectively reviewed.

Effects of Remimazolam vs. Sevoflurane Anesthesia on Intraoperative Hemodynamics in Patients with Gastric Cancer Undergoing Robotic Gastrectomy: A Propensity Score-Matched Analysis.

Remimazolam has been suggested to improve the maintenance of hemodynamic stability when compared with other agents used for general anesthesia. This study aimed to compare the effects of remimazolam and sevoflurane anesthesia on hemodynamic stability in patients undergoing robotic gastrectomy. We retrospectively reviewed the electronic medical records of 199 patients who underwent robotic gastrectomy with sevoflurane (n = 135) or remimazolam (n = 64) anesthesia from January to November 2021.

HumanNet v3: an improved database of human gene networks for disease research.

Network medicine has proven useful for dissecting genetic organization of complex human diseases. We have previously published HumanNet, an integrated network of human genes for disease studies. Since the release of the last version of HumanNet, many large-scale protein-protein interaction datasets have accumulated in public depositories.

Human reference gut microbiome catalog including newly assembled genomes from under-represented Asian metagenomes.

Background: Metagenome sampling bias for geographical location and lifestyle is partially responsible for the incomplete catalog of reference genomes of gut microbial species. Thus, genome assembly from currently under-represented populations may effectively expand the reference gut microbiome and improve taxonomic and functional profiling.

Methods: We assembled genomes using public whole-metagenomic shotgun sequencing (WMS) data for 110 and 645 fecal samples from India and Japan, respectively.

BarleyNet: A Network-Based Functional Omics Analysis Server for Cultivated Barley, L.

Cultivated barley ( L.) is one of the most produced cereal crops worldwide after maize, bread wheat, and rice. Barley is an important crop species not only as a food source, but also in plant genetics because it harbors numerous stress response alleles in its genome that can be exploited for crop engineering.

Understanding the immunopathogenesis of autoimmune diseases by animal studies using gene modulation: A comprehensive review.

Autoimmune diseases are clinical syndromes that result from pathogenic inflammatory responses driven by inadequate immune activation by T- and B-cells. Although the exact mechanisms of autoimmune diseases are still elusive, genetic factors also play an important role in the pathogenesis. Recently, with the advancement of understanding of the immunological and molecular basis of autoimmune diseases, gene modulation has become a potential approach for the tailored treatment of autoimmune disorders.

BiomeNet: a database for construction and analysis of functional interaction networks for any species with a sequenced genome.

Motivation: Owing to advanced DNA sequencing and genome assembly technology, the number of species with sequenced genomes is rapidly increasing. The aim of the recently launched Earth BioGenome Project is to sequence genomes of all eukaryotic species on Earth over the next 10 years, making it feasible to obtain genomic blueprints of the majority of animal and plant species by this time. Genetic models of the sequenced species will later be subject to functional annotation, and a comprehensive molecular network should facilitate functional analysis of individual genes and pathways.

VirtualCytometry: a webserver for evaluating immune cell differentiation using single-cell RNA sequencing data.

Motivation: The immune system has diverse types of cells that are differentiated or activated via various signaling pathways and transcriptional regulation upon challenging conditions. Immunophenotyping by flow and mass cytometry are the major approaches for identifying key signaling molecules and transcription factors directing the transition between the functional states of immune cells. However, few proteins can be evaluated by flow cytometry in a single experiment, preventing researchers from obtaining a comprehensive picture of the molecular programs involved in immune cell differentiation.

Network Integrative Genomic and Transcriptomic Analysis of Carbapenem-Resistant Klebsiella pneumoniae Strains Identifies Genes for Antibiotic Resistance and Virulence.

Global increases in the use of carbapenems have resulted in several strains of Gram-negative bacteria acquiring carbapenem resistance, thereby limiting treatment options. is a common carbapenem-resistant pathogenic bacterium that is widely studied to identify novel antibiotic resistance mechanisms and drug targets. Antibiotic-resistant clinical isolates generally harbor many genetic alterations, and the identification of responsible mutations would provide insights into the molecular mechanisms of antibiotic resistance.

MaizeNet: a co-functional network for network-assisted systems genetics in Zea mays.

Maize (Zea mays) has multiple uses in human food, animal fodder, starch and sweetener production and as a biofuel, and is accordingly the most extensively cultivated cereal worldwide. To enhance maize production, genetic factors underlying important agricultural traits, including stress tolerance and flowering, have been explored through forward and reverse genetics approaches. Co-functional gene networks are systems biology resources useful in identifying trait-associated genes in plants by prioritizing candidate genes.

A Genome-Scale Co-Functional Network of Genes Can Accurately Reconstruct Regulatory Circuits Controlled by Two-Component Signaling Systems.

Bacterial species in the genus infect virtually all crop plants. Although many genes involved in virulence have been identified through molecular and cellular studies, the elucidation of virulence-associated regulatory circuits is still far from complete. Functional gene networks have proven useful in generating hypotheses for genetic factors of biological processes in various species.

HumanNet v2: human gene networks for disease research.

Human gene networks have proven useful in many aspects of disease research, with numerous network-based strategies developed for generating hypotheses about gene-disease-drug associations. The ability to predict and organize genes most relevant to a specific disease has proven especially important. We previously developed a human functional gene network, HumanNet, by integrating diverse types of omics data using Bayesian statistics framework and demonstrated its ability to retrieve disease genes.

TRRUST v2: an expanded reference database of human and mouse transcriptional regulatory interactions.

Transcription factors (TFs) are major trans-acting factors in transcriptional regulation. Therefore, elucidating TF-target interactions is a key step toward understanding the regulatory circuitry underlying complex traits such as human diseases. We previously published a reference TF-target interaction database for humans-TRRUST (Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining)-which was constructed using sentence-based text mining, followed by manual curation.

GWAB: a web server for the network-based boosting of human genome-wide association data.

During the last decade, genome-wide association studies (GWAS) have represented a major approach to dissect complex human genetic diseases. Due in part to limited statistical power, most studies identify only small numbers of candidate genes that pass the conventional significance thresholds (e.g.

Function-driven discovery of disease genes in zebrafish using an integrated genomics big data resource.

Whole exome sequencing (WES) accelerates disease gene discovery using rare genetic variants, but further statistical and functional evidence is required to avoid false-discovery. To complement variant-driven disease gene discovery, here we present function-driven disease gene discovery in zebrafish (Danio rerio), a promising human disease model owing to its high anatomical and genomic similarity to humans. To facilitate zebrafish-based function-driven disease gene discovery, we developed a genome-scale co-functional network of zebrafish genes, DanioNet (www.

COEXPEDIA: exploring biomedical hypotheses via co-expressions associated with medical subject headings (MeSH).

The use of high-throughput array and sequencing technologies has produced unprecedented amounts of gene expression data in central public depositories, including the Gene Expression Omnibus (GEO). The immense amount of expression data in GEO provides both vast research opportunities and data analysis challenges. Co-expression analysis of high-dimensional expression data has proven effective for the study of gene functions, and several co-expression databases have been developed.

Network-assisted investigation of virulence and antibiotic-resistance systems in Pseudomonas aeruginosa.

Pseudomonas aeruginosa is a Gram-negative bacterium of clinical significance. Although the genome of PAO1, a prototype strain of P. aeruginosa, has been extensively studied, approximately one-third of the functional genome remains unknown.

MouseNet v2: a database of gene networks for studying the laboratory mouse and eight other model vertebrates.

Laboratory mouse, Mus musculus, is one of the most important animal tools in biomedical research. Functional characterization of the mouse genes, hence, has been a long-standing goal in mammalian and human genetics. Although large-scale knockout phenotyping is under progress by international collaborative efforts, a large portion of mouse genome is still poorly characterized for cellular functions and associations with disease phenotypes.

TRRUST: a reference database of human transcriptional regulatory interactions.

The reconstruction of transcriptional regulatory networks (TRNs) is a long-standing challenge in human genetics. Numerous computational methods have been developed to infer regulatory interactions between human transcriptional factors (TFs) and target genes from high-throughput data, and their performance evaluation requires gold-standard interactions. Here we present a database of literature-curated human TF-target interactions, TRRUST (transcriptional regulatory relationships unravelled by sentence-based text-mining, http://www.

FlyNet: a versatile network prioritization server for the Drosophila community.

Drosophila melanogaster (fruit fly) has been a popular model organism in animal genetics due to the high accessibility of reverse-genetics tools. In addition, the close relationship between the Drosophila and human genomes rationalizes the use of Drosophila as an invertebrate model for human neurobiology and disease research. A platform technology for predicting candidate genes or functions would further enhance the usefulness of this long-established model organism for gene-to-phenotype mapping.