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Differential Network Analysis Reveals Regulatory Patterns in Neural Stem Cell Fate Decision Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2021-01-13 Jiang Xie, Yiting Yin, Fuzhang Yang, Jiamin Sun, Jiao Wang
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A Novel Protein Mapping Method for Predicting the Protein Interactions in COVID-19 Disease by Deep Learning Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2021-01-12 Talha Burak Alakus, Ibrahim Turkoglu
The new type of corona virus (SARS-COV-2) emerging in Wuhan, China has spread rapidly to the world and has become a pandemic. In addition to having a significant impact on daily life, it also shows its effect in different areas, including public health and economy. Currently, there is no vaccine or antiviral drug available to prevent the COVID-19 disease. Therefore, determination of protein interactions
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A Radiomics Signature to Quantitatively Analyze COVID-19-Infected Pulmonary Lesions Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2021-01-07 Jiajun Qiu, Shaoliang Peng, Jin Yin, Junren Wang, Jingwen Jiang, Zhenlin Li, Huan Song, Wei Zhang
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Automatic Detection of Genetics and Genomics of Eye Disease Using Deep Assimilation Learning Algorithm Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2021-01-04 Mohamed Yacin Sikkandar
Diabetic retinopathy (DR) is one of the most prevalent genetic diseases in human and it is caused by damage to the blood vessels in the eye retina. If it is undetected and untreated at right time, it can lead to vision loss. There are many medical imaging and processing technologies to improve the diagnostic process of DR to overcome the lack of human experts. In the existing image processing methods
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A machine learning-based framework for diagnosis of COVID-19 from chest X-ray images Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2021-01-02 Jawad Rasheed, Alaa Ali Hameed, Chawki Djeddi, Akhtar Jamil, Fadi Al-Turjman
Corona virus disease (COVID-19) acknowledged as a pandemic by the WHO and mankind all over the world is vulnerable to this virus. Alternative tools are needed that can help in diagnosis of the coronavirus. Researchers of this article investigated the potential of machine learning methods for automatic diagnosis of corona virus with high accuracy from X-ray images. Two most commonly used classifiers
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Ultra-Fast Computation of Excited-States Spectra for Large Systems: Ultraviolet and Fluorescence Spectra of Proteins Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-11-13 Yonggang Liu, Jianjie Xu, Li Han, Qiangqiang Liu, Yunfan Yang, Zeren Li, Zhongyuan Lu, Hang Zhang, Tengxiao Guo, Qiao Liu
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Mathematical Modeling of Calcium Oscillatory Patterns in a Neuron Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-11-10 Devanshi D. Dave, Brajesh Kumar Jha
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Deep-Learning-Based Segmentation and Localization of White Matter Hyperintensities on Magnetic Resonance Images Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-11-02 Wenhao Jiang, Fengyu Lin, Jian Zhang, Taowei Zhan, Peng Cao, Silun Wang
White matter magnetic resonance hyperintensities of presumed vascular origin, which could be widely observed in elderly people, and has significant importance in multiple neurological studies. Quantitative measurement usually relies heavily on manual or semi-automatic delineation and intuitive localization, which is time-consuming and observer-dependent. Current automatic quantification methods focus
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Correlations Between Phenotypes and Biological Process Ontologies in Monogenic Human Diseases Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-10-28 Chenfang Zhang, Georgi Z. Genchev, Dennis Bergau, Hui Lu
A substantial body of research is focused to improve the understanding of the relationship between genotypes and phenotypes. Genotype–phenotype studies have shown promise in improving disease diagnosis in humans and identification of specific clinical phenotypes may be helpful in developing more effective therapeutic and diagnostic strategies. To expand on the existing paradigm of evaluating genotypes
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Predicting Hot Spot Residues at Protein–DNA Binding Interfaces Based on Sequence Information Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-10-17 Lingsong Yao, Huadong Wang, Yannan Bin
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Network Pharmacology Analysis to Uncover the Potential Mechanisms of Lycium barbarum on Colorectal Cancer Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-10-13 Yi Lu, Jiachen Sun, Minhui Hu, Xianhe Kong, Weijie Zhong, Chujun Li
Background Studies have shown that extracts from Lycium barbarum exerted protective effects against colorectal cancer (CRC) cells. We used the network pharmacology method to determine the effects of L. barbarum on CRC and to predict core targets, biological functions, pathways, and mechanisms of action. Method We obtained the active compounds and their targets in L. barbarum via use of the Traditional
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PendoTMBase: A Database for Plant Endogenous Target Mimics Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-09-30 Jiacong Deng, Qingyun Li, Likun Huang, Weiqi Tang, Kehui Zheng, Jiqiang Yan, Weiren Wu
With 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
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Theoretical Research on Excited States: Ultraviolet and Fluorescence Spectra of Aromatic Amino Acids. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-09-26 Yonggang Liu,Jianjie Xu,Li Han,Qiangqiang Liu,Yunfan Yang,Zeren Li,Zhongyuan Lu,Hang Zhang,Tengxiao Guo,Qiao Liu
Using 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)
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Popular Computational Tools Used for miRNA Prediction and Their Future Development Prospects. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-09-21 Tianyang Yu,Na Xu,Neshatul Haque,Chang Gao,Wenhua Huang,Zunnan Huang
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COVID19XrayNet: A Two-Step Transfer Learning Model for the COVID-19 Detecting Problem Based on a Limited Number of Chest X-Ray Images. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-09-21 Ruochi Zhang,Zhehao Guo,Yue Sun,Qi Lu,Zijian Xu,Zhaomin Yao,Meiyu Duan,Shuai Liu,Yanjiao Ren,Lan Huang,Fengfeng Zhou
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The Landscape of Micro-Inversions Provide Clues for Population Genetic Analysis of Humans. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-09-14 Li Qu,Luotong Wang,Feifei He,Yilun Han,Longshu Yang,May D Wang,Huaiqiu Zhu
Background Variations in the human genome have been studied extensively. However, little is known about the role of micro-inversions (MIs), generally defined as small (< 100 bp) inversions, in human evolution, diversity, and health. Depicting the pattern of MIs among diverse populations is critical for interpreting human evolutionary history and obtaining insight into genetic diseases. Results In this
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A Novel Human Diabetes Biomarker Recognition Approach Using Fuzzy Rough Multigranulation Nearest Neighbour Classifier Model. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-09-12 Swarup Kr Ghosh,Anupam Ghosh
The selection of gene identifier from microarray databases is a challenging task since microarray contains large number of gene attributes for a few samples. 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
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Study on the Mechanisms of Banxia Xiexin Decoction in Treating Diabetic Gastroparesis Based on Network Pharmacology. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-09-10 Tingchao Wu,Rensong Yue,Liang Li,Mingmin He
In China, Banxia Xiexin decoction (BXD) is applied to treat diabetic gastroparesis (DGP), but its key active ingredients and mechanisms against DGP are unclear. 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
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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. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-09-10 Elham Amjad,Solmaz Asnaashari,Babak Sokouti,Siavoush Dastmalchi
Breast cancer, as one of the most common diseases threatening the women's life, has attracted serious attention of the clinical and biomedical researchers worldwide. The genome-based studies along with their registered GEO datasets are frequent in the literature. Since several methodologies have been developed for analyzing and identifying gene biomarkers, it is necessary to evaluate their robustness
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Comprehensive Analysis of Long Non-coding RNA-Associated Competing Endogenous RNA Network in Duchenne Muscular Dystrophy. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-09-02 Xiaoxue Xu,Yuehan Hao,Shuang Xiong,Zhiyi He
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Review of Artificial Intelligence Applications and Algorithms for Brain Organoid Research. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-08-24 Jiayidaer Badai,Qian Bu,Le Zhang
The 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
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Fully Automatic Arteriovenous Segmentation in Retinal Images via Topology-Aware Generative Adversarial Networks. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-07-28 Jingwen Yang,Xinran Dong,Yu Hu,Qingsheng Peng,Guihua Tao,Yangming Ou,Hongmin Cai,Xiaohong Yang
Retinal 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
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Shiny-DEG: A Web Application to Analyze and Visualize Differentially Expressed Genes in RNA-seq. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-07-14 Sufang Wang,Yu Zhang,Congzhan Hu,Nu Zhang,Michael Gribskov,Hui Yang
Abstract RNA-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
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Impact of IL28 Genotypes and Modeling the Interactions of HCV Core Protein on Treatment of Hepatitis C. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-07-12 Tayebeh Hashempour,Behzad Dehghani,Zahra Musavi,Javad Moayedi,Zahra Hasanshahi,Jamal Sarvari,Seyed Younes Hosseini,Ebrahim Hosseini,Maryam Moeini,Shahin Merat
Background Mutations in the core CVR region of hepatitis C virus (HCV) and polymorphisms of interleukin 28B (IL28B) are associated with progression toward liver disease and in response to therapy. In addition, interactions of the core protein with some cell interactors can be related to HCV liver damage. Aim This study aimed to evaluate the effect of core mutations as well as IL28B polymorphism on
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Efficient System Wide Metabolic Pathway Comparisons in Multiple Microbes Using Genome to KEGG Orthology (G2KO) Pipeline Tool. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-07-06 Chandrakant Joshi,Swati Sharma,Neil MacKinnon,Shyam Kumar Masakapalli
Comparison 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 networks
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Phylogenetic Analysis and Structural Perspectives of RNA-Dependent RNA-Polymerase Inhibition from SARs-CoV-2 with Natural Products. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-07-03 Abbas Khan,Mazhar Khan,Shoaib Saleem,Zainib Babar,Arif Ali,Abdul Aziz Khan,Zain Sardar,Fahad Hamayun,Syed Shujait Ali,Dong-Qing Wei
Abstract Most 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
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AC-Caps: Attention Based Capsule Network for Predicting RBP Binding Sites of LncRNA. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-06-22 Jinmiao Song,Shengwei Tian,Long Yu,Yan Xing,Qimeng Yang,Xiaodong Duan,Qiguo Dai
Long 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
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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. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-06-12 V Saravanan,R Manikandan,K S Maharasan,R Ramesh
In 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
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GAD: A Python Script for Dividing Genome Annotation Files into Feature-Based Files. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-06-10 Norhan Yasser,Ahmed Karam
Nowadays, 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
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ProtPCV: A Fixed Dimensional Numerical Representation of Protein Sequence to Significantly Reduce Sequence Search Time. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-06-10 Manoj Kumar Pal,Tapobrata Lahiri,Rajnish Kumar
Protein 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
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Next-Generation Sequencing Data Analysis on Pool-Seq and Low-Coverage Retinoblastoma Data. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-06-09 Gülistan Özdemir Özdoğan,Hilal Kaya
Next-generation sequencing (NGS) is related to massively parallel or deep deoxyribonucleic acid (DNA) sequencing technology which has revolutionized genomic researches in recent years. Although the cost of generating NGS data was decreased compared to the one at the time of emerging this technology, its cost might still be somewhat a problem. Hence, new strategies as pool-seq and low-coverage NGS data
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Retinal Image Analysis for Ocular Disease Prediction Using Rule Mining Algorithms. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-06-08 R Karthiyayini,N Shenbagavadivu
Medical 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
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Deep Learning Based Drug Screening for Novel Coronavirus 2019-nCov. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-06-01 Haiping Zhang,Konda Mani Saravanan,Yang Yang,Md Tofazzal Hossain,Junxin Li,Xiaohu Ren,Yi Pan,Yanjie Wei
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
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Combining SVM and ECOC for Identification of Protein Complexes from Protein Protein Interaction Networks by Integrating Amino Acids' Physical Properties and Complex Topology. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-05-21 Amen Faridoon,Aisha Sikandar,Muhammad Imran,Saman Ghouri,Misba Sikandar,Waseem Sikandar
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
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Feature Selection for Microarray Data Classification Using Hybrid Information Gain and a Modified Binary Krill Herd Algorithm. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-05-21 Ge Zhang,Jincui Hou,Jianlin Wang,Chaokun Yan,Junwei Luo
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
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Finding Community Modules for Brain Networks Combined Uniform Design with Fruit Fly Optimization Algorithm. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-05-18 Jie Zhang,Junhong Feng,Yifang Yang,Jian-Hong Wang
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
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An Effective Convolutional Neural Network for Classifying Red Blood Cells in Malaria Diseases. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-05-11 Quan Quan,Jianxin Wang,Liangliang Liu
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
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Identification of CpG Islands in DNA Sequences Using Short-Time Fourier Transform. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-05-11 Pardeep Garg,Sunildatt Sharma
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
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Metatax: Metataxonomics with a Compi-Based Pipeline for Precision Medicine. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-04-30 Osvaldo Graña-Castro,Hugo López-Fernández,Alba Nogueira-Rodríguez,Florentino Fdez-Riverola,Fátima Al-Shahrour,Daniel Glez-Peña
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
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Gene Biomarkers Derived from Clinical Data of Hepatocellular Carcinoma. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-04-15 Jiaming Qi,Jiaxing Zhou,Xu-Qing Tang,Yaolai Wang
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
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Clustering-Based Hybrid Approach for Identifying Quantitative Multidimensional Associations Between Patient Attributes, Drugs and Adverse Drug Reactions. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-03-30 Yogita,Jerry W Sangma,S R Ngamwal Anal,Vipin Pal
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
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Towards Predicting Risk of Coronary Artery Disease from Semi-Structured Dataset Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-03-19 Smita Roy, Asif Ekbal, Samrat Mondal, Maunendra Sankar Desarkar, Shubham Chattopadhyay
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
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A Novel Index of Contact Frequency from Noise Protein-Protein Interaction Data Help for Accurate Interface Residue Pair Prediction. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-03-17 Yanfen Lyu,He Huang,Xinqi Gong
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
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iPseU-Layer: Identifying RNA Pseudouridine Sites Using Layered Ensemble Model. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-03-13 Yashuang Mu,Ruijun Zhang,Lidong Wang,Xiaodong Liu
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
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Single-Cell Clustering Based on Shared Nearest Neighbor and Graph Partitioning. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-02-22 Xiaoshu Zhu,Jie Zhang,Yunpei Xu,Jianxin Wang,Xiaoqing Peng,Hong-Dong Li
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)
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An Integrated Systems Biology and Network-Based Approaches to Identify Novel Biomarkers in Breast Cancer Cell Lines Using Gene Expression Data. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-02-13 Abbas Khan,Zainab Rehman,Huma Farooque Hashmi,Abdul Aziz Khan,Muhammad Junaid,Abrar Mohammad Sayaf,Syed Shujait Ali,Fakhr Ul Hassan,Wang Heng,Dong-Qing Wei
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
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Identification of Key Regulatory Genes and Pathways in Prefrontal Cortex of Alzheimer's Disease. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-01-31 Fuzhang Yang,Xin Diao,Fushuai Wang,Quanwei Wang,Jiamin Sun,Yan Zhou,Jiang Xie
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
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A Network Pharmacology-Based Study of the Molecular Mechanisms of Shaoyao-Gancao Decoction in Treating Parkinson's Disease. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-01-31 Liting Li,Haiyan Qiu,Mimi Liu,Yongming Cai
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
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DNA Mismatch Repair Deficiency Detection in Colorectal Cancer by a New Microsatellite Instability Analysis System. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-01-25 Shafei Wu,Xiaoding Liu,Jing Wang,Weixun Zhou,Mei Guan,Yuanyuan Liu,Junyi Pang,Tao Lu,Liangrui Zhou,Xiaohua Shi,Huanwen Wu,Zhiyong Liang,Xuan Zeng
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
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PPLK+C: A Bioinformatics Tool for Predicting Peptide Ligands of Potassium Channels Based on Primary Structure Information. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-01-07 Jorge Félix Beltrán Lissabet,Lisandra Herrera Belén,Jorge G Farias
Potassium 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
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Revealing the Mechanism of EGCG, Genistein, Rutin, Quercetin, and Silibinin Against hIAPP Aggregation via Computational Simulations Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2020-01-01 Yu Wang, Yonghui Lv, Liang Jin, Guizhao Liang
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
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Q-Nuc: a bioinformatics pipeline for the quantitative analysis of nucleosomal profiles Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2019-12-16 Yuan Wang, Qiu Sun, Jie Liang, Hua Li, Daniel M. Czajkowsky, Zhifeng Shao
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
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CytoMegaloVirus Infection Database: A Public Omics Database for Systematic and Comparable Information of CMV. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2019-12-07 Aman Chandra Kaushik,Aamir Mehmood,Arnav Kumar Upadhyay,Shalinee Paul,Shubham Srivastava,Prayuv Mali,Yi Xiong,Xiaofeng Dai,Dong-Qing Wei,Shakti Sahi
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
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Plant miRNA–lncRNA Interaction Prediction with the Ensemble of CNN and IndRNN Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2019-12-06 Peng Zhang, Jun Meng, Yushi Luan, Chanjuan Liu
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
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AGONOTES: A Robot Annotator for Argonaute Proteins. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2019-11-18 Lixu Jiang,Min Yu,Yuwei Zhou,Zhongjie Tang,Ning Li,Juanjuan Kang,Bifang He,Jian Huang
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
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Counting Kmers for Biological Sequences at Large Scale. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2019-11-16 Jianqiu Ge,Jintao Meng,Ning Guo,Yanjie Wei,Pavan Balaji,Shengzhong Feng
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
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A Machine Learning-Based QSAR Model for Benzimidazole Derivatives as Corrosion Inhibitors by Incorporating Comprehensive Feature Selection. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2019-09-06 Youquan Liu,Yanzhi Guo,Wengang Wu,Ying Xiong,Chuan Sun,Li Yuan,Menglong Li
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
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QTL-BSA: A Bulked Segregant Analysis and Visualization Pipeline for QTL-seq. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2019-08-08 Sanling Wu,Jie Qiu,Qikang Gao
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
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Estimation of Probability Distribution and Its Application in Bayesian Classification and Maximum Likelihood Regression. Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2019-07-17 Hao Dai,Wei Wang,Qin Xu,Yi Xiong,Dong-Qing Wei
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
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Development of an Interactive Web Application "Shiny App for Frequency Analysis on Homo sapiens Genome (SAFA-HsG)". Interdiscip. Sci. Comput. Life Sci. (IF 1.512) Pub Date : 2019-07-03 Balamurugan Sivaprakasam,Prasanna Sadagopan
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