Network Pharmacology Analysis to Uncover the Potential Mechanisms of Lycium barbarum on Colorectal Cancer
ConclusionOur work successfully predicted the functioning ingredients and potential targets ofL. barbarum in CRC and illustrated the potential pathways and mechanisms comprehensively. Nevertheless, these results still call for in vitro and in vivo experiments to validate. (Source: Interdisciplinary Sciences, Computational Life Sciences)
Source: Interdisciplinary Sciences, Computational Life Sciences - October 13, 2020 Category: Bioinformatics Source Type: research

PendoTMBase: A Database for Plant Endogenous Target Mimics
AbstractWith fast-evolving next-generation sequencing technology, a great amount of plant genome and transcriptome data are becoming available. Due to the availability of mature microRNA (miRNA) sequence information from the miRBase (release 21) database, it is possible to predict endogenous target mimics (eTMs) in plant by searching seed-matched target sites. We identified a total of 2669 non-redundant eTM records in 43 plant species to create a specialized web-based database platform. The platform is named PendoTMBase, which can provide details of the eTMs. Predicted pairing structure between eTMs and their target miRNA,...
Source: Interdisciplinary Sciences, Computational Life Sciences - September 29, 2020 Category: Bioinformatics Source Type: research

Theoretical Research on Excited States: Ultraviolet and Fluorescence Spectra of Aromatic Amino Acids
AbstractUsing Gaussian and Orca, UV and fluorescence spectra of three amino acids (Tyr: Tyrosine, Trp: Tryptophan, Phe: Phenylalanine) were calculated by different functionals (B3LYP, BP86, wB97X). The spectra calculated by BP86 are consistent with the experiments. UV spectra peak of Tyr is 255  nm (Exp. 275 nm, Δλ = 20 nm), Trp is 279 nm (Exp. 277 nm, Δλ = 2 nm), and Phe is 275 nm (Exp. 257 nm, Δλ = 18 nm). Fluorescence spectra peak of Trp is 341 nm (Exp. 350 nm, Δλ =&...
Source: Interdisciplinary Sciences, Computational Life Sciences - September 25, 2020 Category: Bioinformatics Source Type: research

COVID19XrayNet: A Two-Step Transfer Learning Model for the COVID-19 Detecting Problem Based on a Limited Number of Chest X-Ray Images
This study proposed a two-step transfer learning pipeline and a deep residual network framework COVID19XrayNet for the COVID-19 detection problem based on chest X-ray images. COVID19XrayNet firstly tunes the transferred model on a large dataset of chest X-ray images, which is further tuned using a small dataset of annotated chest X-ray images. The final model achieved 0.9108 accuracy. The experimental data also suggested that the model may be improved with more training samples being released.Graphic abstractCOVID19XrayNet, a two-step transfer learning framework designed for biomedical images. (Source: Interdisciplinary Sc...
Source: Interdisciplinary Sciences, Computational Life Sciences - September 20, 2020 Category: Bioinformatics Source Type: research

Popular Computational Tools Used for miRNA Prediction and Their Future Development Prospects
AbstractMicroRNAs (miRNAs) are 19 –24 nucleotide (nt)-long noncoding, single-stranded RNA molecules that play significant roles in regulating the gene expression, growth, and development of plants and animals. From the year that miRNAs were first discovered until the beginning of the twenty-first century, researchers used experime ntal methods such as cloning and sequencing to identify new miRNAs and their roles in the posttranscriptional regulation of protein synthesis. Later, in the early 2000s, informatics approaches to the discovery of new miRNAs began to be implemented. With increasing knowledge about miRNA, mor...
Source: Interdisciplinary Sciences, Computational Life Sciences - September 20, 2020 Category: Bioinformatics Source Type: research

The Landscape of Micro-Inversions Provide Clues for Population Genetic Analysis of Humans
AbstractBackgroundVariations in the human genome have been studied extensively. However, little is known about the role of micro-inversions (MIs), generally defined as small (
Source: Interdisciplinary Sciences, Computational Life Sciences - September 13, 2020 Category: Bioinformatics Source Type: research

A Novel Human Diabetes Biomarker Recognition Approach Using Fuzzy Rough Multigranulation Nearest Neighbour Classifier Model
This article proposes a novel fuzzy-rough set-based gene expression features selection using fuzzy-rough reduct under multi-granular space for human diabetes patient. Firstly, fuzzy multi-granular gain has been computed from the expression datasets via fuzzy entropy which reduces the dimension of the database. Thereafter, the features have been selected from microarray using the fuzzy rough reduct and information gain with respect to their expression patterns. To reduce the computational cost, a decision making scheme has been designed using a rough approximation of a fuzzy concept in the field of multi-granulation framewo...
Source: Interdisciplinary Sciences, Computational Life Sciences - September 11, 2020 Category: Bioinformatics Source Type: research

Impact of Gene Biomarker Discovery Tools Based on Protein –Protein Interaction and Machine Learning on Performance of Artificial Intelligence Models in Predicting Clinical Stages of Breast Cancer
In this study, three well-known biomarker identification methods (i.e., ClusterOne, MCODE, and BioDiscML) were employed in order to identify the potential biomarkers. Then, the methods were ranked and evaluated using nonlinear classification models developed based on the identified sets of biomarkers. A combined BC microarray dataset consisting of GSE124647, GSE124646, and GSE15852 was used as training set, and two test datasets, GSE15852 and GSE25066, were used for the performance measurement of the trained models. The validation of the proposed models was carried out internally (leave-one-out, fivefold and tenfold cross-...
Source: Interdisciplinary Sciences, Computational Life Sciences - September 9, 2020 Category: Bioinformatics Source Type: research

Study on the Mechanisms of Banxia Xiexin Decoction in Treating Diabetic Gastroparesis Based on Network Pharmacology
This study is designated to reveal the molecular mechanisms of BXD in treating DGP by adopting a creative approach known as network pharmacology to explore the active ingredients and therapeutic targets of BXD. In our study, 730 differentially expressed genes of DGP were obtained, and 30 potential targets of BXD against DGP were screened out (including ADRB2, DRD1, FOS, MMP9, FOSL1, FOSL2, JUN, MAP2, DRD2, MYC, F3, CDKN1A, IL6, NFKBIA, ICAM1, CCL2, SELE, DUOX2, MGAM, THBD, SERPINE1, ALOX5, CXCL11, CXCL2, CXCL10, RUNX2, CD40LG, C1QB, MCL1, and ADCYAP1). Based on the findings, BXD contains 60 compounds with therapeutic effec...
Source: Interdisciplinary Sciences, Computational Life Sciences - September 9, 2020 Category: Bioinformatics Source Type: research

Comprehensive Analysis of Long Non-coding RNA-Associated Competing Endogenous RNA Network in Duchenne Muscular Dystrophy
In conclusion, our latest bioinformatic analysis demonstrated that lncRNA is likely involved in DMD. This work highlights the importance of lncRNA and provides new insights for exploring the molecular mechanism of DMD.Graphic abstractThe created ceRNA network contained 6 lncRNA nodes, 69 mRNA nodes, 27 miRNA nodes and 102 edges, while four hub lncRNAs (XIST,AL132709,LINC00310,ALDH1L1-AS2) were uncovered. Remarkably, KEGG analysis indicated that targeted mRNAs in the network were mainly enriched in “microRNAs in cancer” and “proteoglycans in cancer”. Our study may offer novel perspectives on the path...
Source: Interdisciplinary Sciences, Computational Life Sciences - September 1, 2020 Category: Bioinformatics Source Type: research

Review of Artificial Intelligence Applications and Algorithms for Brain Organoid Research
AbstractThe human brain organoid is a miniature three-dimensional tissue culture that can simulate the structure and function of the brain in an in vitro culture environment. Although we consider that human brain organoids could be used to understand brain development and diseases, experimental models of human brain organoids are so highly variable that we apply artificial intelligence (AI) techniques to investigate the development mechanism of the human brain. Therefore, this study briefly reviewed commonly used AI applications for human brain organoid-magnetic resonance imaging, electroencephalography, and gene editing t...
Source: Interdisciplinary Sciences, Computational Life Sciences - August 23, 2020 Category: Bioinformatics Source Type: research

Fully Automatic Arteriovenous Segmentation in Retinal Images via Topology-Aware Generative Adversarial Networks
AbstractRetinal image contains rich information on the blood vessel and is highly related to vascular diseases. Fully automatic and accurate identification of arteries and veins from the complex background of retinal images is essential for analyzing eye-relevant diseases, and monitoring progressive eye diseases. However, popular methods, including deep learning-based models, performed unsatisfactorily in preserving the connectivity of both the arteries and veins. The results were shown to be disconnected or overlapped by the twos and thus manual calibration was needed to refine the results. To tackle the problem, this pap...
Source: Interdisciplinary Sciences, Computational Life Sciences - July 27, 2020 Category: Bioinformatics Source Type: research

Shiny-DEG: A Web Application to Analyze and Visualize Differentially Expressed Genes in RNA-seq
AbstractRNA-seq analysis has become one of the most widely used methods for biological and medical experiments, aiming to identify differentially expressed genes at a large scale. However, due to lack of programming skills and statistical background, it is difficult for biologists including faculty and students to fully understand what the RNA-seq results are and how to interpret them. In recent years, even though, there are several programs or websites that assist researchers to analyze and visualize NGS results, they have several limitations. Therefore, Shiny-DEG, a web application that facilitates the exploration and vi...
Source: Interdisciplinary Sciences, Computational Life Sciences - July 13, 2020 Category: Bioinformatics Source Type: research

Impact of IL28 Genotypes and Modeling the Interactions of HCV Core Protein on Treatment of Hepatitis C
ConclusionGenerally, mutations in all core CVR regions in all patients showed a relationship between such substitutions and higher liver enzymes that can result in advanced liver disease progression in HCV infected patients. Furthermore, immunoinformatics analysis determined the possible immunodominant regions to be considered in HCV vaccine designs. Furthermore, no association between SVR and IL28B polymorphism was shown. In silico analysis determined modification sites, structures, B-cell epitopes of core protein and interactions with several interactors can lead to persistent  HCV infection in the cell and the prog...
Source: Interdisciplinary Sciences, Computational Life Sciences - July 11, 2020 Category: Bioinformatics Source Type: research

Efficient System Wide Metabolic Pathway Comparisons in Multiple Microbes Using Genome to KEGG Orthology (G2KO) Pipeline Tool
AbstractComparison of system-wide metabolic pathways among microbes provides valuable insights of organisms ’ metabolic capabilities that can further assist in rationally screening organisms in silico for various applications. In this work, we present a much needed, efficient and user-friendly Genome to KEGG Orthology (G2KO) pipeline tool that facilitates efficient comparison of system wide metabolic ne tworks of multiple organisms simultaneously. The optimized strategy primarily involves automatic retrieval of the KEGG Orthology (KO) identifiers of user defined organisms from the KEGG database followed by overlaying...
Source: Interdisciplinary Sciences, Computational Life Sciences - July 5, 2020 Category: Bioinformatics Source Type: research

Phylogenetic Analysis and Structural Perspectives of RNA-Dependent RNA-Polymerase Inhibition from SARs-CoV-2 with Natural Products
AbstractMost recently, an outbreak of severe pneumonia caused by the infection of SARS-CoV-2, a novel coronavirus first identified in Wuhan, China, imposes serious threats to public health. Upon infecting host cells, coronaviruses assemble a multi-subunit RNA-synthesis complex of viral non-structural proteins (nsp) responsible for the replication and transcription of the viral genome. Therefore, the role and inhibition of nsp12 are indispensable. A cryo-EM structure of RdRp from SARs-CoV-2 was used to identify novel drugs from Northern South African medicinal compounds database (NANPDB) by using computational virtual scree...
Source: Interdisciplinary Sciences, Computational Life Sciences - July 2, 2020 Category: Bioinformatics Source Type: research

AC-Caps: Attention Based Capsule Network for Predicting RBP Binding Sites of LncRNA
AbstractLong non-coding RNA(lncRNA) is one of the non-coding RNAs longer than 200 nucleotides and it has no protein encoding function. LncRNA plays a key role in many biological processes. Studying the RNA-binding protein (RBP) binding sites on the lncRNA chain helps to reveal epigenetic and post-transcriptional mechanisms, to explore the physiological and pathological processes of cancer, and to discover new therapeutic breakthroughs. To improve the recognition rate of RBP binding sites and reduce the experimental time and cost, many calculation methods based on domain knowledge to predict RBP binding sites have emerged. ...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 21, 2020 Category: Bioinformatics Source Type: research

Optimized Attribute Selection Using Artificial Plant (AP) Algorithm with ESVM Classifier (AP-ESVM) and Improved Singular Value Decomposition (ISVD)-Based Dimensionality Reduction for Large Micro-array Biological Data
AbstractIn the tremendous field of the bioinformatics look into, enormous volume of genetic information has been produced. Higher throughput gadgets are made accessible at lower cost made the age of Big data. In a time of developing information multifaceted nature and volume and the approach of huge information, feature selection has a key task to carry out in decreasing high dimensionality in AI issues. Dealing with such huge data has turned out to be incredibly testing strategy for choosing the exact features in enormous medical databases. Large clinical data frequently comprise of an enormous number of identifiers of th...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 11, 2020 Category: Bioinformatics Source Type: research

ProtPCV: A Fixed Dimensional Numerical Representation of Protein Sequence to Significantly Reduce Sequence Search Time
AbstractProtein sequence is a wealth of experimental information which is yet to be exploited to extract information on protein homologues. Consequently, it is observed from publications that dynamic programming, heuristics and HMM profile-based alignment techniques along with the alignment free techniques do not directly utilize ordered profile of physicochemical properties of a protein to identify its homologue. Also, it is found that these works lack crucial bench-marking or validation in absence of which their incorporation in search engines may appears to be questionable. In this direction this research approach offer...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 9, 2020 Category: Bioinformatics Source Type: research

GAD: A Python Script for Dividing Genome Annotation Files into Feature-Based Files
AbstractNowadays, the manipulation and analysis of genomic data stored in publicly accessible repositories have become a daily task in genomics and bioinformatics laboratories. Due to the enormous advancement in the field of genome sequencing and the emergence of many projects, bioinformaticians have pushed for the creation of a variety of programs and pipelines that will automatically analyze such big data, in particular the pipelines of gene annotation. Dealing with annotation files using easy and simple programs is very important, particularly for non-developers, enhancing the genomic data analysis acceleration. One of ...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 9, 2020 Category: Bioinformatics Source Type: research

Next-Generation Sequencing Data Analysis on Pool-Seq and Low-Coverage Retinoblastoma Data
This study provides a guideline for performing NGS data analysis pipeline on pool-seq and low-coverage sequencing data in conjunction. To get more conclusive outcomes of these two strategies, we recommend using cancer data having higher mutation rates and larger pools. (Source: Interdisciplinary Sciences, Computational Life Sciences)
Source: Interdisciplinary Sciences, Computational Life Sciences - June 8, 2020 Category: Bioinformatics Source Type: research

Retinal Image Analysis for Ocular Disease Prediction Using Rule Mining Algorithms
AbstractMedical image processing is now gaining a significant momentum in clinical situation to undertake diagnosis of different anatomical defects. However, with regard to eye diseases, there is no such well-defined image processing technique in medical image analysis. The scope of this study is to automate computer analysis of ocular disease-related retinal images, which may ease the job of ophthalmologists to rule out the diseased condition. In this present work, eye images are subjected for developing a reliable tool for processing the eye retinal fundus images. The primary objective is to effectively probe retinal ima...
Source: Interdisciplinary Sciences, Computational Life Sciences - June 7, 2020 Category: Bioinformatics Source Type: research

Deep Learning Based Drug Screening for Novel Coronavirus 2019-nCov
AbstractA 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 takes a much longer time to develop a drug using traditional methods. For 2019-nCoV, it is now better to rely on some alternative methods such as deep learning to develop drugs that can combat such a disease effectively...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 31, 2020 Category: Bioinformatics Source Type: research

Combining SVM and ECOC for Identification of Protein Complexes from Protein Protein Interaction Networks by Integrating Amino Acids ’ Physical Properties and Complex Topology
AbstractProtein 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 amino acid sequence and identified dense sub graphs as complexes from PPI network by considering density and degree statistics. Biological information evaluate the common features for performing a particular biologica...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 20, 2020 Category: Bioinformatics Source Type: research

Feature Selection for Microarray Data Classification Using Hybrid Information Gain and a Modified Binary Krill Herd Algorithm
AbstractDue 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, we propose a novel feature selection strategy in this paper, called IG-MBKH. A pre-screening method of feature ranking which is based on information gain (IG) and an improved binary krill herd (MBKH) algorithm are i...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 20, 2020 Category: Bioinformatics Source Type: research

Finding Community Modules for Brain Networks Combined Uniform Design with Fruit Fly Optimization Algorithm
AbstractThere 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 combines the uniform design and the fruit fly optimization algorithm (FOA); therefore, we called it as UFOA. It makes the utmost of their respective merits of the uniform design and the FOA, so as to acquire the feasib...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 17, 2020 Category: Bioinformatics Source Type: research

An Effective Convolutional Neural Network for Classifying Red Blood Cells in Malaria Diseases
In this study, we propose an efficient and novel classification network named Attentive Dense Circular Net (ADCN) which based on Convolutional Neural Networks (CNN). The ADCN is inspired by the ideas of residual and dense networks and combines with the attention mechanism. We train and evaluate our proposed model on a publicly available red blood cells (RBC) dataset and compare ADCN with several well-established CNN models. Compared to other best performing CNN model in our experiments, ADCN shows superiority in all performance criteria such as accuracy (97.47% vs 94.61%), sensitivity (97.86% vs 95.20%) and specificity (97...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 10, 2020 Category: Bioinformatics Source Type: research

Identification of CpG Islands in DNA Sequences Using Short-Time Fourier Transform
AbstractIn 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 islands in DNA sequences. The key contributions of this work are (i) extraction of the periodicity feature associated with CpG islands using Short-time Fourier transform (ii) a short-time Fourier transform-based algorith...
Source: Interdisciplinary Sciences, Computational Life Sciences - May 10, 2020 Category: Bioinformatics Source Type: research

Metatax: Metataxonomics with a Compi-Based Pipeline for Precision Medicine
AbstractThe 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 of the 16S rRNA genetic marker. Precision medicine attempts to find relationships between the microbiota and the risk of acquiring cancer, and design new thera pies targeting bacteria. Flexible and portable bi...
Source: Interdisciplinary Sciences, Computational Life Sciences - April 29, 2020 Category: Bioinformatics Source Type: research

Gene Biomarkers Derived from Clinical Data of Hepatocellular Carcinoma
This study, therefore, suggests that the abnormal expression of those eight genes may be taken as gene biomarkers of HCC. (Source: Interdisciplinary Sciences, Computational Life Sciences)
Source: Interdisciplinary Sciences, Computational Life Sciences - April 14, 2020 Category: Bioinformatics Source Type: research

Clustering-Based Hybrid Approach for Identifying Quantitative Multidimensional Associations Between Patient Attributes, Drugs and Adverse Drug Reactions
AbstractThe 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 out several interesting associations when it comes to analysis of multidimensional data which may include multiple patient attributes, drugs and adverse drug reactions. In the present work, a clustering-based hybrid a...
Source: Interdisciplinary Sciences, Computational Life Sciences - March 29, 2020 Category: Bioinformatics Source Type: research

Towards Predicting Risk of Coronary Artery Disease from Semi-Structured Dataset
AbstractMany 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 result is often not acceptable in this domain. In this paper, we have analyzed a partially annotated coronary artery disease (CAD) dataset which was originally in a semi-structured form. We have created a set of some well...
Source: Interdisciplinary Sciences, Computational Life Sciences - March 18, 2020 Category: Bioinformatics Source Type: research

A Novel Index of Contact Frequency from Noise Protein –Protein Interaction Data Help for Accurate Interface Residue Pair Prediction
AbstractProtein –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 r esidue pairs. Here, we extract the interface residue–residue contacts from the decoys in the ZDOCK protein–protein complex decoy set with RMSD mostly larger than 3 Å. To accurately compute the interface residue–residue contacts, we define a new constant called interface r...
Source: Interdisciplinary Sciences, Computational Life Sciences - March 16, 2020 Category: Bioinformatics Source Type: research

iPseU-Layer: Identifying RNA Pseudouridine Sites Using Layered Ensemble Model
AbstractPseudouridine 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 to develop an efficient pseudouridine site identification method based on machine learning is very important both in academic research and drug development. Motived by this, we present an effective layered ensemble model ...
Source: Interdisciplinary Sciences, Computational Life Sciences - March 12, 2020 Category: Bioinformatics Source Type: research

Single-Cell Clustering Based on Shared Nearest Neighbor and Graph Partitioning
AbstractClustering 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) and shared nearest neighbor (SNN) without considering the structure information of graph. Here, to improve the clustering accuracy, we present a novel method for single-cell clustering, called structural shared nearest n...
Source: Interdisciplinary Sciences, Computational Life Sciences - February 21, 2020 Category: Bioinformatics Source Type: research

An Integrated Systems Biology and Network-Based Approaches to Identify Novel Biomarkers in Breast Cancer Cell Lines Using Gene Expression Data
AbstractBreast 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 as disease states, intensities based on gene expression as well as protein–protein interactions. To find prospective biomarkers in breast cancer, we first identified differentially expressed genes (DEGs) s...
Source: Interdisciplinary Sciences, Computational Life Sciences - February 12, 2020 Category: Bioinformatics Source Type: research

A Network Pharmacology-Based Study of the Molecular Mechanisms of Shaoyao-Gancao Decoction in Treating Parkinson ’s Disease
AbstractParkinson ’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 effec tive drugs without side effects. The present study applied a creative approach called network pharmacology to explore the active compounds and therapeutic targets of Shaoyao-Gancao Decoction (SYGCD) for treating PD. We identified a total of 48 active compounds mediating 30 PD-related targets to exe...
Source: Interdisciplinary Sciences, Computational Life Sciences - January 30, 2020 Category: Bioinformatics Source Type: research

Identification of Key Regulatory Genes and Pathways in Prefrontal Cortex of Alzheimer ’s Disease
This study aims to identify the potential therapeutic target genes and related pathways in PFC of AD. First, differential expression analyses were performed on transcriptome microarray of PFC between AD specimens and non-AD controls. Second, protein–protein interaction net works were constructed based on the identified differentially expressed genes to explore candidate therapeutic target genes. Finally, these candidate genes were validated through biological experiments. The enrichment analyses showed that the differentially expressed genes were significantly enriche d in protein functions and pathways related to AD...
Source: Interdisciplinary Sciences, Computational Life Sciences - January 30, 2020 Category: Bioinformatics Source Type: research

DNA Mismatch Repair Deficiency Detection in Colorectal Cancer by a New Microsatellite Instability Analysis System
ConclusionsThe colorectal cancer can be classified according to MSI status accurately by ProDx ® MSI. More cases with MSI-High feature may be revealed by ProDx® MSI than by previous test systems in colorectal cancer. (Source: Interdisciplinary Sciences, Computational Life Sciences)
Source: Interdisciplinary Sciences, Computational Life Sciences - January 24, 2020 Category: Bioinformatics Source Type: research

PPLK + C: A Bioinformatics Tool for Predicting Peptide Ligands of Potassium Channels Based on Primary Structure Information
AbstractPotassium channels play a key role in regulating the flow of ions through the plasma membrane, orchestrating many cellular processes including cell volume regulation, hormone secretion and electrical impulse formation. Ligand peptides of potassium channels are molecules used in basic and applied research and are now considered promising alternatives in the treatment of many diseases, such as cardiovascular diseases and cancer. Currently, there are various bioinformatics tools focused on the prediction of peptides with different activities. However, none of the current tools can predict ligand peptides of potassium ...
Source: Interdisciplinary Sciences, Computational Life Sciences - January 6, 2020 Category: Bioinformatics Source Type: research

Revealing the Mechanism of EGCG, Genistein, Rutin, Quercetin, and Silibinin Against hIAPP Aggregation via Computational Simulations
AbstractTo 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 detailed mechanisms to inhibit hIAPP aggregation remain unclear. Here, we explore the mechanisms of the five flavonoids against hIAPP aggregation by molecular docking and molecular dynamics simulations. We show that the...
Source: Interdisciplinary Sciences, Computational Life Sciences - December 31, 2019 Category: Bioinformatics Source Type: research

Q-Nuc: a bioinformatics pipeline for the quantitative analysis of nucleosomal profiles
AbstractNucleosomal 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 their randomness and relative occupancy level. Applying this method to published data, we find on average  ~ 3-fold differences in the degree of positional randomness between regions typically considered &...
Source: Interdisciplinary Sciences, Computational Life Sciences - December 15, 2019 Category: Bioinformatics Source Type: research

CytoMegaloVirus Infection Database: A Public Omics Database for Systematic and Comparable Information of CMV
AbstractCytoMegaloVirus (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 a comprehensive database having exhaustive information regarding CMV, its infections and therapies to be available on a single platform. Thus, we propose a newly designed database that includes all the information from...
Source: Interdisciplinary Sciences, Computational Life Sciences - December 6, 2019 Category: Bioinformatics Source Type: research

Plant miRNA –lncRNA Interaction Prediction with the Ensemble of CNN and IndRNN
AbstractNon-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 limitations of human factors, the prediction accuracy and reliability of traditional feature-based classification methods are often affected. Besides, the structure of plant ncRNA is complex. This paper proposes an ensem...
Source: Interdisciplinary Sciences, Computational Life Sciences - December 5, 2019 Category: Bioinformatics Source Type: research

AGONOTES: A Robot Annotator for Argonaute Proteins
AbstractThe 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 becoming available, computational tools for identifying and annotating argonaute proteins are urgently needed. We introduce AGONOTES (Argonaute Notes). It is a web service especially designed for identifying and an...
Source: Interdisciplinary Sciences, Computational Life Sciences - November 17, 2019 Category: Bioinformatics Source Type: research

Counting Kmers for Biological Sequences at Large Scale
AbstractCounting 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 the memory and computing capacity of single computing node, and how to process it efficiently is a challenge on a high-performance computing cluster. As such, we propose SWAPCounter, a highly scalable distributed approa...
Source: Interdisciplinary Sciences, Computational Life Sciences - November 15, 2019 Category: Bioinformatics Source Type: research

A Systems Biology Roadmap to Decode mTOR Control System in Cancer
AbstractMechanistic target of rapamycin (mTOR) is a critical protein in the regulation of cell fate decision making, especially in cancer cells. mTOR acts as a signal integrator and is one of the main elements of interactions among the pivotal cellular processes such as cell death, autophagy, metabolic reprogramming, cell growth, and cell cycle. The temporal control of these processes is essential for the cellular homeostasis and dysregulation of mTOR signaling pathway results in different phenotypes, including aging, oncogenesis, cell survival, cell growth, senescence, quiescence, and cell death. In this paper, we have pr...
Source: Interdisciplinary Sciences, Computational Life Sciences - September 16, 2019 Category: Bioinformatics Source Type: research

A Machine Learning-Based QSAR Model for Benzimidazole Derivatives as Corrosion Inhibitors by Incorporating Comprehensive Feature Selection
ConclusionBased on our model, 6 new benzimidazole molecules were designed and their IE values predicted by this model indicate that two of them have high potential as outstanding corrosion inhibitors. (Source: Interdisciplinary Sciences, Computational Life Sciences)
Source: Interdisciplinary Sciences, Computational Life Sciences - September 3, 2019 Category: Bioinformatics Source Type: research

Integrative Analysis of Multi-Genomic Data for Kidney Renal Cell Carcinoma
AbstractAccounting for nine out of ten kidney cancers, kidney renal cell carcinoma (KIRC) is by far the most common type of kidney cancer. In view of limited and ineffective available therapies, understanding the genetic basis of disease becomes important for better diagnosis and treatment. The present studies are based on a single type of  genomic data. These studies do not consider interactions between genomic data types and their underlying biological relationships in the disease. However, the current availability of multiple genomic data and the possibility of combining it have facilitated a better ...
Source: Interdisciplinary Sciences, Computational Life Sciences - August 7, 2019 Category: Bioinformatics Source Type: research

QTL-BSA: A Bulked Segregant Analysis and Visualization Pipeline for QTL-seq
AbstractIn 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 research community. However, there is no publicly available user friendly software for the identification and visualization. Hence, we developed a tool named QTL-BSA (QTL-bulked segregant analysis and visualization pipel...
Source: Interdisciplinary Sciences, Computational Life Sciences - August 5, 2019 Category: Bioinformatics Source Type: research