Advances in Bioinformatics最新文献_第4页

Structural Prediction and Mutational Analysis of Rv3906c Gene of Mycobacterium tuberculosis H₃₇Rv to Determine Its Essentiality in Survival. 对结核分枝杆菌 H37Rv 的 Rv3906c 基因进行结构预测和突变分析，以确定其在存活中的重要性。

Advances in Bioinformatics Pub Date : 2018-08-15 eCollection Date: 2018-01-01 DOI: 10.1155/2018/6152014

Md Amjad Beg, Shivangi, Sonu Chand Thakur, Laxman S Meena

{"title":"Structural Prediction and Mutational Analysis of Rv3906c Gene of Mycobacterium tuberculosis H37Rv to Determine Its Essentiality in Survival.","authors":"Md Amjad Beg, Shivangi, Sonu Chand Thakur, Laxman S Meena","doi":"10.1155/2018/6152014","DOIUrl":"10.1155/2018/6152014","url":null,"abstract":"The emergence of tuberculosis is at the peak; therefore to station it at its lower level we hereby try bioinformatics approach against Mycobacterium tuberculosis [M. tuberculosis] pathogenesis. Rv3906c is a conserved hypothetical gene of M. tuberculosis and contains many GTP binding protein motif DXXG which demonstrate that this gene might be processed in a GTP binding or in GTP hydrolyzing manner. This gene shows interaction with its adjacent genes as well as pcnA which is a polymerase and localized in the extracellular region and found to be a soluble protein. Rv3906c has binding pockets for calcium atom at various positions which prove that calcium might have some role during the process of this gene. GTP binding protein motif DXXG is present in various positions and calcium binds at this site with a C-score of 0.25. Mutational analysis on this motif shows the large decrease of stability after mutation of aspartate residue with glycine. Stress conditions like pH and temperature also change stability of the protein. A decrease in stability at this position might play a role in inhibition of survival of the pathogen. These computational studies of this gene might be a successful step towards drug development against tuberculosis.","PeriodicalId":39059,"journal":{"name":"Advances in Bioinformatics","volume":"2018 ","pages":"6152014"},"PeriodicalIF":0.0,"publicationDate":"2018-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6114228/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36466013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Gaussian Fuzzy Number for STR-DNA Similarity Calculation Involving Familial and Tribal Relationships. 涉及家族和部落关系的STR-DNA相似性计算的高斯模糊数。

Advances in Bioinformatics Pub Date : 2018-07-29 eCollection Date: 2018-01-01 DOI: 10.1155/2018/8602513

Maria Susan Anggreainy, M Rahmat Widyanto, Belawati H Widjaja, Nurtami Soedarsono

{"title":"Gaussian Fuzzy Number for STR-DNA Similarity Calculation Involving Familial and Tribal Relationships.","authors":"Maria Susan Anggreainy, M Rahmat Widyanto, Belawati H Widjaja, Nurtami Soedarsono","doi":"10.1155/2018/8602513","DOIUrl":"https://doi.org/10.1155/2018/8602513","url":null,"abstract":"We performed locus similarity calculation by measuring fuzzy intersection between individual locus and reference locus and then performed CODIS STR-DNA similarity calculation. The fuzzy intersection calculation enables a more robust CODIS STR-DNA similarity calculation due to imprecision caused by noise produced by PCR machine. We also proposed shifted convoluted Gaussian fuzzy number (SCGFN) and Gaussian fuzzy number (GFN) to represent each locus value as improvement of triangular fuzzy number (TFN) as used in previous research. Compared to triangular fuzzy number (TFN), GFN is more realistic to represent uncertainty of locus information because the distribution is assumed to be Gaussian. Then, the original Gaussian fuzzy number (GFN) is convoluted with distribution of certain ethnic locus information to produce the new SCGFN which more represents ethnic information compared to original GFN. Experiments were done for the following cases: people with family relationships, people of the same tribe, and certain tribal populations. The statistical test with analysis of variance (ANOVA) shows the difference in similarity between SCGFN, GFN, and TFN with a significant level of 95%. The Tukey method in ANOVA shows that SCGFN yields a higher similarity which means being better than the GFN and TFN methods. The proposed method enables CODIS STR-DNA similarity calculation which is more robust to noise and performed better CODIS similarity calculation involving familial and tribal relationships.","PeriodicalId":39059,"journal":{"name":"Advances in Bioinformatics","volume":"2018 ","pages":"8602513"},"PeriodicalIF":0.0,"publicationDate":"2018-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2018/8602513","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36434449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Creation of Individual Scientific Concept-Centered Semantic Maps Based on Automated Text-Mining Analysis of PubMed. 基于PubMed自动文本挖掘分析的个体科学概念中心语义图的创建。

Advances in Bioinformatics Pub Date : 2018-07-26 eCollection Date: 2018-01-01 DOI: 10.1155/2018/4625394

Ekaterina Ilgisonis, Andrey Lisitsa, Valerya Kudryavtseva, Elena Ponomarenko

引用次数: 0

Big Data Management for Healthcare Systems: Architecture, Requirements, and Implementation. 医疗保健系统的大数据管理:架构、需求和实现。

Advances in Bioinformatics Pub Date : 2018-06-21 eCollection Date: 2018-01-01 DOI: 10.1155/2018/4059018

Naoual El Aboudi, Laila Benhlima

引用次数: 87

A Novel Framework for Ab Initio Coarse Protein Structure Prediction. Ab Initio粗蛋白结构预测的新框架。

Advances in Bioinformatics Pub Date : 2018-06-20 DOI: 10.1155/2018/7607384

Sandhya Parasnath Dubey, S Balaji, N Gopalakrishna Kini, M Sathish Kumar

{"title":"A Novel Framework for Ab Initio Coarse Protein Structure Prediction.","authors":"Sandhya Parasnath Dubey, S Balaji, N Gopalakrishna Kini, M Sathish Kumar","doi":"10.1155/2018/7607384","DOIUrl":"10.1155/2018/7607384","url":null,"abstract":"Hydrophobic-Polar model is a simplified representation of Protein Structure Prediction (PSP) problem. However, even with the HP model, the PSP problem remains NP-complete. This work proposes a systematic and problem specific design for operators of the evolutionary program which hybrids with local search hill climbing, to efficiently explore the search space of PSP and thereby obtain an optimum conformation. The proposed algorithm achieves this by incorporating the following novel features: (i) new initialization method which generates only valid individuals with (rather than random) better fitness values; (ii) use of probability-based selection operators that limit the local convergence; (iii) use of secondary structure based mutation operator that makes the structure more closely to the laboratory determined structure; and (iv) incorporating all the above-mentioned features developed a complete two-tier framework. The developed framework builds the protein conformation on the square and triangular lattice. The test has been performed using benchmark sequences, and a comparative evaluation is done with various state-of-the-art algorithms. Moreover, in addition to hypothetical test sequences, we have tested protein sequences deposited in protein database repository. It has been observed that the proposed framework has shown superior performance regarding accuracy (fitness value) and speed (number of generations needed to attain the final conformation). The concepts used to enhance the performance are generic and can be used with any other population-based search algorithm such as genetic algorithm, ant colony optimization, and immune algorithm.","PeriodicalId":39059,"journal":{"name":"Advances in Bioinformatics","volume":"2018 ","pages":"7607384"},"PeriodicalIF":0.0,"publicationDate":"2018-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2018/7607384","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36328364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

In Silico Characterization and Structural Modeling of Dermacentor andersoni p36 Immunosuppressive Protein. 安德氏真皮真皮免疫抑制蛋白的硅表征和结构建模。

Advances in Bioinformatics Pub Date : 2018-04-08 eCollection Date: 2018-01-01 DOI: 10.1155/2018/7963401

Martin Omulindi Oyugi, Johnson Kangethe Kinyua, Esther Nkirote Magiri, Milcah Wagio Kigoni, Evenilton Pessoa Costa, Naftaly Wang'ombe Githaka

{"title":"In Silico Characterization and Structural Modeling of Dermacentor andersoni p36 Immunosuppressive Protein.","authors":"Martin Omulindi Oyugi, Johnson Kangethe Kinyua, Esther Nkirote Magiri, Milcah Wagio Kigoni, Evenilton Pessoa Costa, Naftaly Wang'ombe Githaka","doi":"10.1155/2018/7963401","DOIUrl":"https://doi.org/10.1155/2018/7963401","url":null,"abstract":"Ticks cause approximately $17-19 billion economic losses to the livestock industry globally. Development of recombinant antitick vaccine is greatly hindered by insufficient knowledge and understanding of proteins expressed by ticks. Ticks secrete immunosuppressant proteins that modulate the host's immune system during blood feeding; these molecules could be a target for antivector vaccine development. Recombinant p36, a 36 kDa immunosuppressor from the saliva of female Dermacentor andersoni, suppresses T-lymphocytes proliferation in vitro. To identify potential unique structural and dynamic properties responsible for the immunosuppressive function of p36 proteins, this study utilized bioinformatic tool to characterize and model structure of D. andersoni p36 protein. Evaluation of p36 protein family as suitable vaccine antigens predicted a p36 homolog in Rhipicephalus appendiculatus, the tick vector of East Coast fever, with an antigenicity score of 0.7701 that compares well with that of Bm86 (0.7681), the protein antigen that constitute commercial tick vaccine Tickgard™. Ab initio modeling of the D. andersoni p36 protein yielded a 3D structure that predicted conserved antigenic region, which has potential of binding immunomodulating ligands including glycerol and lactose, found located within exposed loop, suggesting a likely role in immunosuppressive function of tick p36 proteins. Laboratory confirmation of these preliminary results is necessary in future studies.","PeriodicalId":39059,"journal":{"name":"Advances in Bioinformatics","volume":"2018 ","pages":"7963401"},"PeriodicalIF":0.0,"publicationDate":"2018-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2018/7963401","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36178249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Framework for Parallel Preprocessing of Microarray Data Using Hadoop. 基于Hadoop的微阵列数据并行预处理框架。

Advances in Bioinformatics Pub Date : 2018-03-29 eCollection Date: 2018-01-01 DOI: 10.1155/2018/9391635

Amirhossein Sahlabadi, Ravie Chandren Muniyandi, Mahdi Sahlabadi, Hossein Golshanbafghy

{"title":"Framework for Parallel Preprocessing of Microarray Data Using Hadoop.","authors":"Amirhossein Sahlabadi, Ravie Chandren Muniyandi, Mahdi Sahlabadi, Hossein Golshanbafghy","doi":"10.1155/2018/9391635","DOIUrl":"https://doi.org/10.1155/2018/9391635","url":null,"abstract":"Nowadays, microarray technology has become one of the popular ways to study gene expression and diagnosis of disease. National Center for Biology Information (NCBI) hosts public databases containing large volumes of biological data required to be preprocessed, since they carry high levels of noise and bias. Robust Multiarray Average (RMA) is one of the standard and popular methods that is utilized to preprocess the data and remove the noises. Most of the preprocessing algorithms are time-consuming and not able to handle a large number of datasets with thousands of experiments. Parallel processing can be used to address the above-mentioned issues. Hadoop is a well-known and ideal distributed file system framework that provides a parallel environment to run the experiment. In this research, for the first time, the capability of Hadoop and statistical power of R have been leveraged to parallelize the available preprocessing algorithm called RMA to efficiently process microarray data. The experiment has been run on cluster containing 5 nodes, while each node has 16 cores and 16 GB memory. It compares efficiency and the performance of parallelized RMA using Hadoop with parallelized RMA using affyPara package as well as sequential RMA. The result shows the speed-up rate of the proposed approach outperforms the sequential approach and affyPara approach.","PeriodicalId":39059,"journal":{"name":"Advances in Bioinformatics","volume":"2018 ","pages":"9391635"},"PeriodicalIF":0.0,"publicationDate":"2018-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2018/9391635","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36126845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

An Efficient Approach in Analysis of DNA Base Calling Using Neural Fuzzy Model. 一种基于神经模糊模型的DNA碱基调用分析方法。

Advances in Bioinformatics Pub Date : 2017-01-01 Epub Date: 2017-01-31 DOI: 10.1155/2017/3686025

Safa A Hameed, Raed I Hamed

引用次数: 1

Empirical Comparison of Visualization Tools for Larger-Scale Network Analysis. 大规模网络分析可视化工具的实证比较。

Advances in Bioinformatics Pub Date : 2017-01-01 Epub Date: 2017-07-18 DOI: 10.1155/2017/1278932

Georgios A Pavlopoulos, David Paez-Espino, Nikos C Kyrpides, Ioannis Iliopoulos

引用次数: 50

Computational Analysis of Gynura bicolor Bioactive Compounds as Dipeptidyl Peptidase-IV Inhibitor. Gynura双色生物活性化合物作为二肽基肽酶- iv抑制剂的计算分析。

Advances in Bioinformatics Pub Date : 2017-01-01 Epub Date: 2017-08-08 DOI: 10.1155/2017/5124165

Lina Rozano, Muhammad Redha Abdullah Zawawi, Muhamad Aizuddin Ahmad, Indu Bala Jaganath

{"title":"Computational Analysis of Gynura bicolor Bioactive Compounds as Dipeptidyl Peptidase-IV Inhibitor.","authors":"Lina Rozano, Muhammad Redha Abdullah Zawawi, Muhamad Aizuddin Ahmad, Indu Bala Jaganath","doi":"10.1155/2017/5124165","DOIUrl":"https://doi.org/10.1155/2017/5124165","url":null,"abstract":"The inhibition of dipeptidyl peptidase-IV (DPPIV) is a popular route for the treatment of type-2 diabetes. Commercially available gliptin-based drugs such as sitagliptin, anagliptin, linagliptin, saxagliptin, and alogliptin were specifically developed as DPPIV inhibitors for diabetic patients. The use of Gynura bicolor in treating diabetes had been reported in various in vitro experiments. However, an understanding of the inhibitory actions of G. bicolor bioactive compounds on DPPIV is still lacking and this may provide crucial information for the development of more potent and natural sources of DPPIV inhibitors. Evaluation of G. bicolor bioactive compounds for potent DPPIV inhibitors was computationally conducted using Lead IT and iGEMDOCK software, and the best free-binding energy scores for G. bicolor bioactive compounds were evaluated in comparison with the commercial DPPIV inhibitors, sitagliptin, anagliptin, linagliptin, saxagliptin, and alogliptin. Drug-likeness and absorption, distribution, metabolism, and excretion (ADME) analysis were also performed. Based on molecular docking analysis, four of the identified bioactive compounds in G. bicolor, 3-caffeoylquinic acid, 5-O-caffeoylquinic acid, 3,4-dicaffeoylquinic acid, and trans-5-p-coumaroylquinic acid, resulted in lower free-binding energy scores when compared with two of the commercially available gliptin inhibitors. The results revealed that bioactive compounds in G. bicolor are potential natural inhibitors of DPPIV.","PeriodicalId":39059,"journal":{"name":"Advances in Bioinformatics","volume":"2017 ","pages":"5124165"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2017/5124165","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35373105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15