In silico prediction of Severe Acute Respiratory Syndrome Coronavirus 2 main protease cleavage sites.

One of the emerging subjects to combat the SARS-CoV-2 virus is to design accurate and efficient drug such as inhibitors against the viral protease to stop the viral spread. In addition to laboratory investigation of the viral protease, which is fundamental, the in silico research of viral protease such as the protease cleavage site prediction is critically important and urgent. However, this problem has yet to be addressed.

Recurrence of positive SARS-CoV-2 viral RNA in recovered COVID-19 patients during medical isolation observation.

Recently, the recurrence of positive SARS-CoV-2 viral RNA in recovered COVID-19 patients is receiving more attention. Herein we report a cohort study on the follow-up of 182 recovered patients under medical isolation observation. Twenty (10.

Global Analysis of Genes Essential for Francisella tularensis Schu S4 Growth and for Fitness during Competitive Infection of Fischer 344 Rats.

The highly virulent intracellular pathogen is a Gram-negative bacterium that has a wide host range, including humans, and is the causative agent of tularemia. To identify new therapeutic drug targets and vaccine candidates and investigate the genetic basis of virulence in the Fischer 344 rat, we have constructed an Schu S4 transposon library. This library consists of more than 300,000 unique transposon mutants and represents a transposon insertion for every 6 bp of the genome.

A Noise Trimming and Positional Significance of Transposon Insertion System to Identify Essential Genes in Yersinia pestis.

Massively parallel sequencing technology coupled with saturation mutagenesis has provided new and global insights into gene functions and roles. At a simplistic level, the frequency of mutations within genes can indicate the degree of essentiality. However, this approach neglects to take account of the positional significance of mutations - the function of a gene is less likely to be disrupted by a mutation close to the distal ends.

Multi-omic measurement of mutually exclusive loss-of-function enriches for candidate synthetic lethal gene pairs.

Background: Identification of synthetic lethal interactions in cancer cells could offer promising new therapeutic targets. Large-scale functional genomic screening presents an opportunity to test large numbers of cancer synthetic lethal hypotheses. Methods enriching for candidate synthetic lethal targets in molecularly defined cancer cell lines can steer effective design of screening efforts.

Improved prediction of RNA secondary structure by integrating the free energy model with restraints derived from experimental probing data.

Recently, several experimental techniques have emerged for probing RNA structures based on high-throughput sequencing. However, most secondary structure prediction tools that incorporate probing data are designed and optimized for particular types of experiments. For example, RNAstructure-Fold is optimized for SHAPE data, while SeqFold is optimized for PARS data.

Interleukin-27 is differentially associated with HIV viral load and CD4+ T cell counts in therapy-naïve HIV-mono-infected and HIV/HCV-co-infected Chinese.

Human Immunodeficiency Virus (HIV) infection and the resultant Acquired Immunodeficiency Syndrome (AIDS) epidemic are major global health challenges; hepatitis C virus (HCV) co-infection has made the HIV/AIDS epidemic even worse. Interleukin-27 (IL-27), a cytokine which inhibits HIV and HCV replication in vitro, associates with HIV infection and HIV/HCV co-infection in clinical settings. However, the impact of HIV and HCV viral loads on plasma IL-27 expression levels has not been well characterized.

HIV infection and sexual behaviors among non-commercial men who have sex with men at different venues.

The prevalence of HIV infection among men who have sex with men (MSM) has increased rapidly in China. Previous studies suggested that some venue-specific characteristics could significantly affect MSM's sexual behaviors that were related to HIV transmission. Thus, to compare the HIV infection rates and related risky sexual behaviors among MSM at different venues, we conducted a cross-sectional study with time-location sampling in Shenzhen, China.

A comparison of HIV infection and related risk factors between money boys and noncommercial men who have sex with men in Shenzhen, China.

Background: HIV transmission among men who have sex with men (MSM) has become an increasing concern in China. Money boys (MBs) are a subgroup of MSM who sell sex to men. Direct comparison of HIV prevalence and related risk factors between MB and noncommercial MSM (ncMSM) has rarely been done.

Transcriptomic assay of CD8+ T cells in treatment-naïve HIV, HCV-mono-infected and HIV/HCV-co-infected Chinese.

Background: Co-infection with HIV and HCV is very common. It is estimated that over 5 million people are co-infected with HIV and HCV worldwide. Accumulated evidence shows that each virus alters the course of infection of the other one.

[The influence of T lymphocyte activation on HIV-1 susceptibility of Han Chinese].

Objective: To explore the influence of T lymphocyte activation on HIV-1 susceptibility of Han Chinese.

Methods: In 2008, 37 HIV-1 highly exposed persistently seronegative individuals (ESNs) and 101 healthy controls were screened from Shenzhen. Flow cytometer was used to assay the expression difference of HIV-1 infection related co-receptor, the difference between the two groups were analyzed by Mann-Whitney U statistics methods.

An ultra-fast metabolite prediction algorithm.

Small molecules are central to all biological processes and metabolomics becoming an increasingly important discovery tool. Robust, accurate and efficient experimental approaches are critical to supporting and validating predictions from post-genomic studies. To accurately predict metabolic changes and dynamics, experimental design requires multiple biological replicates and usually multiple treatments.

A comparison of HIV infection and related risks among male sex workers in different venues in Shenzhen, China.

Different risks of HIV infection have been reported among different types of male sex workers (MSW). In order to compare the prevalence of HIV infection and related risk behaviors of MSW in different venues in Shenzhen, China, a time-location sampling survey was conducted in 2008. 5.

Predicting sulfotyrosine sites using the random forest algorithm with significantly improved prediction accuracy.

Background: Tyrosine sulfation is one of the most important posttranslational modifications. Due to its relevance to various disease developments, tyrosine sulfation has become the target for drug design. In order to facilitate efficient drug design, accurate prediction of sulfotyrosine sites is desirable.

HIV prevalence and related risk factors among male sex workers in Shenzhen, China: results from a time-location sampling survey.

Background: HIV transmission among men who have sex with men has recently become a major concern in China. Little is known, however, about HIV transmission among male sex workers (MSW). This study aimed to investigate HIV infection prevalence and risk factors among MSW in Shenzhen, China.

[Expression and localization of strong epitope hAFP(542-550); on eukaryotic cytoplasmic membrane].

Aim: To construct the recombinant plasmid of pGPC3-EGFP containing human AFP(542-550) gene, EGFP gene and GPC3 gene to express fusion protein GPC3-hAFP(542-550)-EGFP and to discover its localization on cytoplasmic membrane.

Methods: GPC3 gene was obtained from total RNA of human placental tissues by RT-PCR; After the enhanced green fluorescent protein (EGFP) gene was amplified from pEGFP-N1 plasmid and the gene segment of-KOZAK-GPCN + afp(542-550)-was chemically synthesized, the recombinant plasmid pcDNA3.1(+)/GPCN+afp(542-550)-EGFP-GPCC (pGPC3-EGFP) containing three chimeric genes of strong epitope hAFP(542-550), GPI-anchored protein GPC3 and EGFP was constructed.

A genetic programming approach for Burkholderia pseudomallei diagnostic pattern discovery.

Motivation: Finding diagnostic patterns for fighting diseases like Burkholderia pseudomallei using biomarkers involves two key issues. First, exhausting all subsets of testable biomarkers (antigens in this context) to find a best one is computationally infeasible. Therefore, a proper optimization approach like evolutionary computation should be investigated.

Predict prokaryotic proteins through detecting N-formylmethionine residues in protein sequences using support vector machine.

Identifying prokaryotes in silico is commonly based on DNA sequences. In experiments where DNA sequences may not be immediately available, we need to have a different approach to detect prokaryotes based on RNA or protein sequences. N-formylmethionine (fMet) is known as a typical characteristic of prokaryotes.

Predict collagen hydroxyproline sites using support vector machines.

Collagen hydroxyproline is an important posttranslational modification activity because of its close relationship with various diseases and signaling activities. However, there is no study to date for constructing models for predicting collagen hydroxyproline sites. Support vector machines with two kernel functions (the identity kernel function and the bio-kernel function) have been used for constructing models for predicting collagen hydroxyproline sites in this study.

Peptide bioinformatics: peptide classification using peptide machines.

Peptides scanned from whole protein sequences are the core information for many peptide bioinformatics research such as functional site prediction, protein structure identification, and protein function recognition. In these applications, we normally need to assign a peptide to one of the given categories using a computer model. They are therefore referred to as peptide classification applications.

An unsupervised probabilistic net for health inequalities analysis.

An unsupervised probabilistic net (UPN) is introduced to identify health inequalities among countries according to their health status measured by the collected health indicators. By estimating the underlying probability density function of the health indicators using UPN, countries, which have similar health status, will be categorized into the same cluster. From this, the intercluster health inequalities are identified by the Mahalanobis distance, and the intracluster health inequalities are identified by the diversity within the clusters.

A probabilistic peptide machine for predicting hepatitis C virus protease cleavage sites.

Although various machine learning approaches have been used for predicting protease cleavage sites, constructing a probabilistic model for these tasks is still challenging. This paper proposes a novel algorithm termed as a probabilistic peptide machine where estimating probability density functions and constructing a classifier for predicting protease cleavage sites are combined into one process. The simulation based on experimentally determined Hepatitis C virus (HCV) protease cleavage data has demonstrated the success of this new algorithm.

Bio-basis function neural networks in protein data mining.

Accurately identifying functional sites in proteins is one of the most important topics in bioinformatics and systems biology. In bioinformatics, identifying protease cleavage sites in protein sequences can aid drug/inhibitor design. In systems biology, post-translational protein-protein interaction activity is one of the major components for analyzing signaling pathway activities.