A novel coronavirus, called 2019-nCoV, was recently found in Wuhan, Hubei Province of China, and now is spreading across China and other parts of the world. Although there are some drugs to treat 2019-nCoV, there is no proper scientific evidence about its activity on the virus. It is of high significance to develop a drug that can combat the virus effectively to save valuable human lives. It usually

Protein Complexes plays important role in key functional processes in cells by forming Protein Protein Interaction (PPI) networks. Conventionally, they were determined through experimental approaches. For the sake of saving time and cost reduction, many computational methods have been proposed. Fewer computational approaches take into account significant biological information contained within protein

Due to the presence of irrelevant or redundant data in microarray datasets, capturing potential patterns accurately and directly via existing models is difficult. Feature selection (FS) has become a necessary strategy to identify and screen out the most relevant attributes. However, the high dimensionality of microarray datasets poses a serious challenge to most existing FS algorithms. For this purpose

There are a huge amount of neural units in brain networks. Some of the neural units have tight connection and form neural unit modules. These unit modules are helpful to the disease detection and target therapy. A good method can find neural unit modules accurately and effectively. The study proposes a new algorithm to analyze a brain network and obtain its neural unit modules. The proposed algorithm

Malaria is one of the epidemics that can cause human death. Accurate and rapid diagnosis of malaria is important for treatment. Due to the limited number of data and human factors, the prediction performance and reliability of traditional classification methods are often affected. In this study, we propose an efficient and novel classification network named Attentive Dense Circular Net (ADCN) which

In the era of big data analysis, genomics data analysis is highly needed to extract the hidden information present in the DNA sequences. One of the important hidden features present in the DNA sequences is CpG islands. CpG Islands are important as these are used as gene markers and also these are associated with cancer etc. Therefore, various methods have been reported for the identification of CpG

The human body immune system, metabolism and homeostasis are affected by microbes. Dysbiosis occurs when the homeostatic equilibrium is disrupted due to an alteration in the normal microbiota of the intestine. Dysbiosis can cause cancer, and also affect a patient's ability to respond to treatment. Metataxonomics seeks to identify the bacteria present in a biological sample, based on the sequencing

Hepatocellular carcinoma (HCC) is a common cancer of high mortality, mainly due to the difficulty in diagnosis during its clinical stage. Here we aim to find the gene biomarkers, which are of important significance for diagnosis and treatment. In this work, 3682 differentially expressed genes on HCC were firstly differentiated based on the Cancer Genome Atlas database (TCGA). Co-expression modules

The activity of post-marketing surveillance results in a collection of large amount of data. The analysis of data is very useful for raising early warnings on possible adverse reactions of drugs. Association rule mining techniques have been heavily explored by the research community for identifying binary association between drugs and their adverse effects. But these techniques perform poorly and miss

Many kinds of disease-related data are now available and researchers are constantly attempting to mine useful information out of these. Medical data are not always homogeneous and in structured form, and mostly they are time-stamped data. Thus, special care is required to prevent any kind of information loss during mining such data. Mining medical data is challenging as predicting the non-accurate

Protein-protein interactions are important for most biological processes and have been studied for decades. However, the detailed formation mechanism of protein-protein interaction interface is still ambiguous, which makes it difficult to accurately predict the protein-protein interaction interface residue pairs. Here, we extract the interface residue-residue contacts from the decoys in the ZDOCK protein-protein

Pseudouridine represents one of the most prevalent post-transcriptional RNA modifications. The identification of pseudouridine sites is an essential step toward understanding RNA functions, RNA structure stabilization, translation process, and RNA stability; however, high-throughput experimental techniques remain expensive and time-consuming in lab explorations and biochemical processes. Thus, how

Clustering of single-cell RNA sequencing (scRNA-seq) data enables discovering cell subtypes, which is helpful for understanding and analyzing the processes of diseases. Determining the weight of edges is an essential component in graph-based clustering methods. While several graph-based clustering algorithms for scRNA-seq data have been proposed, they are generally based on k-nearest neighbor (KNN)

Breast cancer is the most common cause of death in women worldwide. Approximately 5%-10% of instances are attributed to mutations acquired from the parents. Therefore, it is highly recommended to design more potential drugs and drug targets to eradicate such complex diseases. Network-based gene expression profiling is a suggested tool for discovering drug targets by incorporating various factors such

Alzheimer's disease (AD) is a neurodegenerative disorder partly induced by dysregulation of different brain regions. Prefrontal cortex (PFC) dysregulation has been reported to associate with mental symptoms such as delusion, apathy, and depression in AD patients. However, the internal mechanisms have not yet been well-understood. This study aims to identify the potential therapeutic target genes and

Parkinson's disease (PD) is another major neurodegenerative disorder following Alzheimer's disease, which not only seriously reduces the survival in patients, affecting patient's quality of life, but also imposes a tremendous burden on families and even the whole society. It is urgent to find out effective drugs without side effects. The present study applied a creative approach called network pharmacology

BACKGROUND Although microsatellite instability (MSI) is most commonly detected in colorectal cancer (CRC), improvement in MSI analysis method can always help us better assessing MSI phenotypes and gaining useful information in challenging cases. The purpose of current study is to explore whether the ProDx® MSI analysis System (ProDx® MSI) can improve MSI classification in CRC. METHODS We compared the

To inhibit hIAPP aggregation and reduce toxicity of its oligomers are one of the potential strategies for the treatment of Type 2 diabetes (T2D). It has been reported that there is an effective inhibitory effect on hIAPP aggregation by five natural flavonoids, including Genistein, Rutin, Quercetin, Epigallocatechin gallate (EGCG), and Silibinin, which are widely found in our daily food. However, the

Nucleosomal profiling is an effective method to determine the positioning and occupancy of nucleosomes, which is essential to understand their roles in genomic processes. However, the positional randomness across the genome and its relationship with nucleosome occupancy remains poorly understood. Here we present a computational method that segments the profile into nucleosomal domains and quantifies

CytoMegaloVirus (CMV) is known to cause infection in humans and may remain dormant throughout the life span of an individual. CMV infection has been reported to be fatal in patients with weak immunity. It is transmitted through blood, saliva, urine, semen and breast milk. Although medications are available to treat the infected patients, there is no cure for CMV. This concern prompted us to construct

Non-coding RNA (ncRNA) plays an important role in regulating biological activities of animals and plants, and the representative ones are microRNA (miRNA) and long non-coding RNA (lncRNA). Recent research has found that predicting the interaction between miRNA and lncRNA is the primary task for elucidating their functional mechanisms. Due to the small scale of data, a large amount of noise, and the

The argonaute protein (Ago) exists in almost all organisms. In eukaryotes, it functions as a regulatory system for gene expression. In prokaryotes, it is a type of defense system against foreign invasive genomes. The Ago system has been engineered for gene silencing and genome editing and plays an important role in biological studies. With an increasing number of genomes and proteomes of various microbes

Counting the abundance of all the distinct kmers in biological sequence data is a fundamental step in bioinformatics. These applications include de novo genome assembly, error correction, etc. With the development of sequencing technology, the sequence data in a single project can reach Petabyte-scale or Terabyte-scale nucleotides. Counting demand for the abundance of these sequencing data is beyond

BACKGROUND Computational prediction of inhibition efficiency (IE) for inhibitor molecules is a crucial supplementary way to design novel molecules that can efficiently inhibit corrosion onto metallic surfaces. PURPOSE Here we are dedicated to developing a new machine learning-based predictor for the inhibition efficiency (IE) of benzimidazole derivatives. METHODS First, a comprehensively numerical

In recent years, the application of Whole Genome Sequencing (WGS) on plants has generated sufficient data for the identification of trait-associated genomic loci or genes. A high-throughput genome-assisted QTL-seq strategy, combined with bulked-segregant analysis and WGS of two bulked populations from a segregating progeny with opposite phenotypic trait values, has gained increasing popularities in

Nonparametric estimation of cumulative distribution function and probability density function of continuous random variables is a basic and central problem in probability theory and statistics. Although many methods such as kernel density estimation have been presented, it is still quite a challenging problem to be addressed to researchers. In this paper, we proposed a new method of spline regression

The web application "Shiny App for Frequency Analysis on Homo sapiens Genome (SAFA-HsG)" was developed using R programming-based bioconductor packages and shiny framework. Through the app, preliminary descriptive data analysis on nucleotide frequency, and CpG island, CpG non-island, and CpG island shores and shelves (downstream and upstream) of human reference genome can be carried out, which will

Primary central nervous system lymphomas (PCNSLs) are rare progressive brain tumors, whose managements are significantly different from other solid tumors, especially glioblastomas. Therefore, an early diagnosis is of great significance. 18F-fluorodeoxyglucose (FDG)-positron emission tomography (PET), which can measure the glucose metabolic rate in the brain, is an increasingly common tool for early

AIM Our aim was to examine existing literature, and determine if there are outcome differences between accelerated corneal collagen cross-linking (A-CXL) and conventional corneal collagen cross-linking (C-CXL). METHODS A systematic review of the literature was conducted examining studies which compared A-CXL to C-CXL. Available studies were combined and the weighted mean difference (WMD) was calculated

The p53 response to DNA damage is closely related to cell fate decisions. P53 preferentially responds to single-stranded breaks (SSBs) exhibiting a graded response when single-stranded breaks (SSBs) and double-stranded breaks (DSBs) coexist. However, how p53 natural preferential response is affected by kinetic parameters remains to be elucidated. Here, based on the hybrid model I, we computationally

Circular RNAs (circRNAs) possess valuable characteristics for both diagnosis and treatment of several human cancers including breast cancer (BC). In this study, we combined several systems, biology tools and approaches to identify influential BC circRNAs, miRNAs, and related mRNAs as the members of competing endogenous RNAs (ceRNAs) networks and related RNA binding proteins (RBPs) to study and decipher

BACKGROUND Nivolumab, a fully human IgG4 programmed cell death-1 checkpoint inhibitor, demonstrated its benefit of prolonged survival in advanced non-small cell lung cancer (NSCLC). However, nivolumab generated unique immune-related adverse events such as thyroid dysfunctions. Herein we assessed nivolumab-induced thyroid dysfunctions in patients with previously treated advanced NSCLC in our hospital

INTRODUCTION GPCR share a common structural feature, i.e., the presence of seven trans-membrane helices having three intracellular and three extracellular loops. The carboxyl terminal is intracellular whereas amino terminal is extracellular. Various conformational changes are observed in structure of GPCR during the binding with ligand, coupling with G protein and interaction with other proteins. In

Histone modifications play critical roles in mammalian development, regulating chromatin structure and gene expression. Dynamic histone modifications among cell types have been shown to associate with changes in mammalian development. However, how to quantitatively measure the histone modification alterations and how histone modifications vary across cell types under different genetic contexts remain

Monoclonal antibodies (mAbs) are one of the robust classes of therapeutic proteins. Their stability, specificity, and high solubility allow the successful development and commercialization of antibody-based drugs. Though with these characteristics, mAbs projects are often suspended due to self- or cross-interaction of monoclonal antibodies. This is one of the main reasons which causes the development

In nearly 50% of patients with drug-induced liver injury, the bile flow is impaired known as cholestasis. Intrahepatic cholestasis of pregnancy (ICP) is the most common liver disease that happens in pregnancy. Some of the clinical symptoms include pruritus, dark urine, and abnormal liver function tests. A rise of serum bile acids is the most accurate diagnostic evidence. ICP may lead to premature birth

BACKGROUND The mechanism of regulation of PD-L1 expression by ALK translocation remains unclear. We detected PD-L1 protein expression and its regulation in lung adenocarcinoma patients with EML4-ALK fusion gene. METHODS PD-L1 and ALK expression at protein level in human lung adenocarcinoma cell lines and tumor tissue specimens was evaluated by immunohistochemistry analysis and Western blotting. The

BACKGROUND PD-1/PD-L1 inhibitors is the important drugs of immunotherapy for malignant tumors. PD-L1 expression is an important biomarker of selecting patients for ICIs therapy. However, the correlation of PD-L1 expression with clinicopathologic features in lung adenocarcinoma remains controversial. METHODS PD-L1 expression was tested using clone SP263 by immunohistochemistry (IHC) on Ventana automated

Autism was a spectrum of multiple complex diseases that required an interdisciplinary group of experts to make a diagnostic decision. Both genetic and environmental factors play essential roles in causing the onset of Autism. Therefore, this study hypothesized that methylomic biomarkers may facilitate the accurate Autism detection. A comprehensive series of biomarker detection algorithms were utilized

Acute lymphoblastic leukemia (ALL) is a hematologic tumor caused by cell cycle aberrations due to accumulating genetic disturbances in the expression of transcription factors (TFs), signaling oncogenes and tumor suppressors. Though survival rate in childhood ALL patients is increased up to 80% with recent medical advances, treatment of adults and childhood relapse cases still remains challenging. Here

Finding DNA sites with high potential for the formation of hairpin/cruciform structures is an important task. Previous works studied the distances between adjacent reversed complement words (symmetric word pairs) and also for non-adjacent words. It was observed that for some words a few distances were favoured (peaks) and that in some distributions there was strong peak regularity. The present work

BACKGROUND The gene order in a eukaryotic genome is not random. Some neighboring genes show specific similarities, while others become separated during evolution. Whole genome duplication events (WGDs) have been recognized as an important evolutionary force. The potential relationship between the separation of neighboring genes and WGDs needs to be investigated. In this study, we investigated whether

Currently, molecular docking is becoming a key tool in drug discovery and molecular modeling applications. The reliability of molecular docking depends on the accuracy of the adopted scoring function, which can guide and determine the ligand poses when thousands of possible poses of ligand are generated. The scoring function can be used to determine the binding mode and site of a ligand, predict binding

Many scientific applications entail solving the subgraph isomorphism problem, i.e., given an input pattern graph, find all the subgraphs of a (usually much larger) target graph that are structurally equivalent to that input. Because subgraph isomorphism is NP-complete, methods to solve it have to use heuristics. This work evaluates subgraph isomorphism methods to assess their computational behavior

In recent years, metabolic engineering has gained central attention in numerous fields of science because of its capability to manipulate metabolic pathways in enhancing the expression of target phenotypes. Due to this, many computational approaches that perform genetic manipulation have been developed in the computational biology field. In metabolic engineering, conventional methods have been utilized

Tuberculosis (TB) is a global infectious disease and one of the ten leading causes of death worldwide. As TB incidence is seasonal, a reliable forecasting model that incorporates both seasonal and trend effects would be useful to improve the prevention and control of TB. In this study, the X12 autoregressive integrated moving average (X12-ARIMA) model was constructed by dividing the sequence into season

Advancement of protein sequencing technologies has led to the production of a huge volume of data that needs to be stored and transmitted. This challenge can be tackled by compression. In this paper, we propose AC, a state-of-the-art method for lossless compression of amino acid sequences. The proposed method works based on the cooperation between finite-context models and substitutional tolerant Markov

Alzheimer's disease (AD) is one of the most common types of dementia among the elderly. Previous studies had revealed that the dysregulation of lncRNAs played important roles in human diseases, including AD. However, there is still a lack of comprehensive analysis of differently expressed long non-coding RNAs (lncRNAs) in different distinct regions related to AD. In present study, we identified a total

Nowadays, bioinformatics is one of the most important areas in modern biology and the creation of high-quality scientific software supporting this recent research area is one of the core activities of many researchers. In this context, high-quality sequence datasets are needed to perform inferences on the evolution of species, genes, and gene families, or to get evidence for adaptive amino acid evolution

Protein-protein interaction (PPI) data is essential to elucidate the complex molecular relationships in living systems, and thus understand the biological functions at cellular and systems levels. The complete map of PPIs that can occur in a living organism is called the interactome. For animals, PPI data is stored in multiple databases (e.g., BioGRID, CCSB, DroID, FlyBase, HIPPIE, HitPredict, HomoMINT

MeCP2 is a protein highly expressed in the brain that participates in the genetic expression and RNA splicing regulation. MeCP2 binds preferably to methylated DNA and other nuclear corepressors to alter chromatin. MECP2 gene mutations can cause rett syndrome (RTT), a severe neurological disorder that affects around one in ten thousand girls. In this paper, Molecular Dynamics (MD) simulations were performed

Complex diseases are generally caused by disorders of biological networks or/and mutations in multiple genes. The efficient and systematic identification of functional modules can not only supply effective diagnosis and treatment in clinic, but also benefit in further in-depth analysis of the pathological mechanism of complex diseases. In this study, we applied the method of differential network to

Accurate gene prediction in metagenomics fragments is a computationally challenging task due to the short-read length, incomplete, and fragmented nature of the data. Most gene-prediction programs are based on extracting a large number of features and then applying statistical approaches or supervised classification approaches to predict genes. In our study, we introduce a convolutional neural network

Many factors, such as endothelial dysfunction, inflammation and hemostatic disturbances, affect formation and progression of atherosclerotic plaque. In our study, we have focused on hemostatic disturbances with particular emphasis on the extrinsic pathways of coagulation. Thrombin is a main enzyme of coagulation and it is engaged in many different subprocesses. It leads to activation of factors of

Useful insight into the evolution of genes and gene families can be provided by the analysis of all available genome datasets rather than just a few, which are usually those of model species. Handling and transforming such datasets into the desired format for downstream analyses is, however, often a difficult and time-consuming task for researchers without a background in informatics. Therefore, we

Dual Oxidase 1 (DUOX1) is a prominent immune system component primarily expressed in esophagus, lungs, skin, and urinary bladder including others. DUOX1 is involved in lactoperoxidase-mediated innate immunity at mucosal surfaces by generation of antimicrobial hypothiocyanite at the apical surface of epithelial lining. Upon detection of bacterial pathogens mainly Pseudomonas aeruginosa, DUOX1 is activated

Trametinib was endorsed by the FDA in 2013 as a single agent for adult melanoma patients. Trametinib inhibits cell growth and proliferation in multiple tumor xenografts by preventing RAF phosphorylation of MEK and thus restricting accumulation of activated MEK. In this study, the focus of investigation was the mechanism of the interaction between trametinib and MEK1/2 via computational simulation.

Development of an effective machine-learning model for T-cell Mycobacterium tuberculosis (M. tuberculosis) epitopes is beneficial for saving biologist's time and effort for identifying epitope in a targeted antigen. Existing NetMHC 2.2, NetMHC 2.3, NetMHC 3.0 and NetMHC 4.0 estimate binding capacity of peptide. This is still a challenge for those servers to predict whether a given peptide is M. tuberculosis

Malicious progression of neurodegeneration is a consequence of toxic aggregates of proteins or peptides such as amyloid beta (Aβ) reported in Alzheimer's disease (AD). These aggregates hinder the electrochemical transmission at neuronal junctions and thus deteriorate neuronal-health by triggering dementia. Electrostatic and hydrophobic interactions among amino-acid residues are the governing principle

HCV p7 protein is a cation-selective ion channel, playing an essential role during the life cycle of HCV viruses. To understand the cation-selective mechanism, we constructed a hexameric model in lipid bilayers of HCV p7 protein for HCB JFH-1 strain, genotype 2a. In this structural model, His9 and Val6 were key factors for the HCV cation-selective ion channel. The histidine residues at position 9 in