mbSparse: an autoencoder-based imputation method to address sparsity in microbiome data.

The involvement of gut microbiota in host physiological activities is crucial, yet the high sparsity of microbiome data, marked by numerous zeros in count matrices, presents huge analytical challenges. To overcome this, we developed mbSparse, an imputation algorithm that leverages deep learning rather than traditional predefined count distributions. Utilizing a feature autoencoder for learning sample representations and a conditional variational autoencoder (CVAE) for data reconstruction, mbSparse effectively integrates these processes to enhance imputation.

SCovid v2.0: a comprehensive resource to decipher the molecular characteristics across tissues in COVID-19 and other human coronaviruses.

Unlabelled: SCovid v2.0 (http://bio-annotation.cn/scovid or http://bio-computing.

SV4GD: a comprehensive structural variation database specially for genetic diseases.

Structural variations (SVs) contribute to a large extent to genomic diversity and are highly relevant for various human genetic diseases. The sensitivity and specificity of SV identification have significantly improved with the development and widespread application of high-throughput sequencing, making clinical diagnosis and treatment more accurate. Therefore, the SV4GD (Structural Variation for Genetic Diseases, https://bio-computing.

Exploring COVID-19 causal genes through disease-specific Cis-eQTLs.

Genome-wide association study (GWAS) analysis has exposed that genetic factors play important roles in COVID-19. Whereas a deeper understanding of the underlying mechanism of COVID-19 was hindered by the lack of expression of quantitative trait loci (eQTL) data specific for disease. To this end, we identified COVID-19-specific cis-eQTLs by integrating nucleotide sequence variations and RNA-Seq data from COVID-19 samples.

Blood microbial analyses reveal long-term effects of SARS-CoV-2 infection on patients who recovered from COVID-19.

Objective: Few symptoms persist for a long time after patients recover from COVID-19, called "long COVID". We explored the potential microbial risk factors for COVID-19 for a deeper understanding and assistance in the follow-up treatment of these sequelae.

Methods: Microbiome re-annotation was performed using whole blood RNA-Seq data collected from recovered COVID-19 patients and healthy controls at multiple time points.

Leveraging molecular quantitative trait loci to comprehend complex diseases/traits from the omics perspective.

Comprehending the molecular basis of quantitative genetic variation is a principal goal for complex diseases or traits. Molecular quantitative trait loci (molQTLs) have made it possible to investigate the effects of genetic variants hiding behind large-scale omics data. A deeper understanding of molQTL is urgently required in light of the multi-dimensionalization of omics data to more fully elucidate the pertinent biological mechanisms.

Genome-wide Mendelian randomization and single-cell RNA sequencing analyses identify the causal effects of COVID-19 on 41 cytokines.

The elevated levels of inflammatory cytokines have attracted much attention during the treatment of COVID-19 patients. The conclusions of current observational studies are often controversial in terms of the causal effects of COVID-19 on various cytokines because of the confounding factors involving underlying diseases. To resolve this problem, we conducted a Mendelian randomization analysis by integrating the GWAS data of COVID-19 and 41 cytokines.

gutMDisorder v2.0: a comprehensive database for dysbiosis of gut microbiota in phenotypes and interventions.

Gut microbiota plays a significant role in maintaining host health, and conversely, disorders potentially lead to dysbiosis, an imbalance in the composition of the gut microbial community. Intervention approaches, such as medications, diets, and several others, also alter the gut microbiota in either a beneficial or harmful direction. In 2020, the gutMDisorder was developed to facilitate researchers in the investigation of dysbiosis of gut microbes as occurs in various disorders as well as with therapeutic interventions.

SCovid: single-cell atlases for exposing molecular characteristics of COVID-19 across 10 human tissues.

SCovid (http://bio-annotation.cn/scovid) aims at providing a comprehensive resource of single-cell data for exposing molecular characteristics of coronavirus disease 2019 (COVID-19) across 10 human tissues. COVID-19, an epidemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been found to be accompanied with multiple-organ failure since its first report in Dec 2019.

gutMGene: a comprehensive database for target genes of gut microbes and microbial metabolites.

gutMGene (http://bio-annotation.cn/gutmgene), a manually curated database, aims at providing a comprehensive resource of target genes of gut microbes and microbial metabolites in humans and mice. Metagenomic sequencing of fecal samples has identified 3.

Non-coding RNAs as Novel Biomarkers in Cancer Drug Resistance.

Chemotherapy is often the primary and most effective anticancer treatment; however, drug resistance remains a major obstacle to it being curative. Recent studies have demonstrated that non-coding RNAs (ncRNAs), especially microRNAs and long non-coding RNAs, are involved in drug resistance of tumor cells in many ways, such as modulation of apoptosis, drug efflux and metabolism, epithelial-to-mesenchymal transition, DNA repair, and cell cycle progression. Exploring the relationships between ncRNAs and drug resistance will not only contribute to our understanding of the mechanisms of drug resistance and provide ncRNA biomarkers of chemoresistance, but will also help realize personalized anticancer treatment regimens.

Prioritizing Disease-Related Microbes Based on the Topological Properties of a Comprehensive Network.

Many microbes are parasitic within the human body, engaging in various physiological processes and playing an important role in human diseases. The discovery of new microbe-disease associations aids our understanding of disease pathogenesis. Computational methods can be applied in such investigations, thereby avoiding the time-consuming and laborious nature of experimental methods.

Dysbiosis of Gut Microbiota in Patients With Acute Myocardial Infarction.

Acute myocardial infarction (AMI) continues as the main cause of morbidity and mortality worldwide. Interestingly, emerging evidence highlights the role of gut microbiota in regulating the pathogenesis of coronary heart disease, but few studies have systematically assessed the alterations and influence of gut microbiota in AMI patients. As one approach to address this deficiency, in this study the composition of fecal microflora was determined from Chinese AMI patients and links between gut microflora and clinical features and functional pathways of AMI were assessed.

Functional alterations caused by mutations reflect evolutionary trends of SARS-CoV-2.

Since the first report of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019, the COVID-19 pandemic has spread rapidly worldwide. Due to the limited virus strains, few key mutations that would be very important with the evolutionary trends of virus genome were observed in early studies. Here, we downloaded 1809 sequence data of SARS-CoV-2 strains from GISAID before April 2020 to identify mutations and functional alterations caused by these mutations.

A comprehensive review for gut microbes: technologies, interventions, metabolites and diseases.

Gut microbes have attracted much more attentions in the recent decade since their essential roles in the development of metabolic diseases, cancer and neurological diseases. Considerable evidence indicates that the metabolism of gut microbes exert influences on intestinal homeostasis and human diseases. Here, we first reviewed two mainstream sequencing technologies involving 16s rRNA sequencing and metagenomic sequencing for gut microbes, and data analysis methods assessing alpha and beta diversity.

gutMDisorder: a comprehensive database for dysbiosis of the gut microbiota in disorders and interventions.

gutMDisorder (http://bio-annotation.cn/gutMDisorder), a manually curated database, aims at providing a comprehensive resource of dysbiosis of the gut microbiota in disorders and interventions. Alterations in the composition of the gut microbial community play crucial roles in the development of chronic disorders.