2016 International Conference on Bioinformatics and Systems Biology (BSB)最新文献_第2页

Predicting conserved domain and structural variations of prenyl transferase sequence variants in Triticum urartu 乌拉尔小麦戊烯基转移酶序列变异的保守域和结构变异预测

2016 International Conference on Bioinformatics and Systems Biology (BSB) Pub Date : 2016-03-04 DOI: 10.1109/BSB.2016.7552155

Mamta Sagar, P. Ramteke, Arvind Kumar Yadav

{"title":"Predicting conserved domain and structural variations of prenyl transferase sequence variants in Triticum urartu","authors":"Mamta Sagar, P. Ramteke, Arvind Kumar Yadav","doi":"10.1109/BSB.2016.7552155","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552155","url":null,"abstract":"Prenyl transferase enzyme is widely distributed among plants. This enzyme catalyses prenylation reaction, that leads to increased flavonoid's activity. In this research, highly conserved polyprenyl patterns have been analysed in plants. Prenyl transferase in Triticum urartu, Oryza sativa japonica and Zea mays share presence of conserved motif LIhDDviDdsgmRRG. This protein share the presence of motif LVlDDimDnsqtRRG in Lupinus albus and Phaseolus vulgaris, both motifs belong to polyprenyl signature 1. Prenyl transferase of Triticum urartu do not contain polyprenyl signature 2. Here, polyprenyl signature 2 motif has been inserted into the protein of Triticum urartu at 273 position, which was extracted from above plants. Structural variations have been analysed using homology modelling after insertion of LGlsFQVvDDIlD and MGtyFQVqDDYlD motifs into protein of Triticum urartu. Modifications in protein do not show any unfavourable changes or disruption in structure. Analysis of Conserved domain Trans-Isoprenyl Diphosphate Synthases shows presence of enhanced substrate binding pocket, catalytic residues in modified Prenyl Transferase.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123847549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cross hybridization to Arabidopsis thaliana array reveals cold stress responsive genes in Lepidium latifolium 拟南芥阵列的交叉杂交揭示了Lepidium latifolium冷胁迫应答基因

2016 International Conference on Bioinformatics and Systems Biology (BSB) Pub Date : 2016-03-04 DOI: 10.1109/BSB.2016.7552120

A. Grover, Sadhana Singh, Basant Ballabh Bhatt, M. Nasim, Pramod Katara

{"title":"Cross hybridization to Arabidopsis thaliana array reveals cold stress responsive genes in Lepidium latifolium","authors":"A. Grover, Sadhana Singh, Basant Ballabh Bhatt, M. Nasim, Pramod Katara","doi":"10.1109/BSB.2016.7552120","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552120","url":null,"abstract":"Cross species hybridization is an attractive option to understand the regulatory mechanisms and transcriptional networks underlying a biological activity, particularly for a non model organism. We have used the same approach to idenitfy cold responsive differentially expressed genes (DEGs) in Lepidium latifolium using Arabidopsis thaliana cDNA array chip. In all, 1315 DEGs were discovered. Putative functions of these cold-responsive genes were explored based on annotations using TAIR database and Blast2GO. Most of the up-regulated gene products were mapped to nucleus (20%) and plastids (15%) showing higher activities as DNA binding proteins, i.e., transcription factors. In all, 45 genes encoding transcription factors were identified belonging most frequently to AP2 family proteins (Seven genes) followed by NAM domain containing proteins (Five genes). Transcription factor binding sites (TFBS) were predicted for 1,100 genes belonging to 78 clusters of co-expressed genes. Interestingly, 50% of these regulatory sites contained a microsatellite repeat. Considering, Lepidium to be a native of high altitude cold regions, the genes identified in this study can be of wide importance to agricultural biotechnologists.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114294472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Molecular interaction and simulation analysis for thyroid cancer pathway 甲状腺癌通路的分子相互作用及模拟分析

2016 International Conference on Bioinformatics and Systems Biology (BSB) Pub Date : 2016-03-04 DOI: 10.1109/BSB.2016.7552127

Chandramani, Vaishali Mishra, S. Chauhan, Manish Kumar Gupta

引用次数: 0

Theoretical model of circular RNA prediction and classification 环状RNA预测和分类的理论模型

2016 International Conference on Bioinformatics and Systems Biology (BSB) Pub Date : 2016-03-04 DOI: 10.1109/BSB.2016.7552122

Rajnish Kumar, T. Lahiri, Gautam Kumar

{"title":"Theoretical model of circular RNA prediction and classification","authors":"Rajnish Kumar, T. Lahiri, Gautam Kumar","doi":"10.1109/BSB.2016.7552122","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552122","url":null,"abstract":"Circular RNAs are reported as new member in RNA world, whose ends are covalently joined and not code for any protein reported till now. Importance of circular RNA as biomarkers for various types of cancers is well reported. Currently, circular RNA candidate prediction is considered as one of the most important steps to further explore role of Circular RNAs in cellular system. Researchers are trying to find circular candidates that are based on the model of events which are responsible for the biogenesis of the circular RNAs. The exact mechanism of circular RNAs biogenesis is not known till now, but there are many proposed methodologies suggested for the genesis of the circular RNAs like exons skipping, back-splicing, exons scrambling, alternate splicing etc. The reported methods till now for finding circular candidate are based on the back splicing event which requires prediction of back splicing sites. This process requires mapping the reads under consideration to their corresponding reference genome. We proposed a de novo-assembly of polyA minus reads based approach that does not requires mapping of reads with reference genome and not depend on prediction of back splice sites to find the circular candidates. We have predicted potential circular RNA candidates by mimicking the output of arrangement of nucleotide sequences after back splicing event. We then perform classifications of circular RNA candidates into coding and non-coding on the basis of origination of candidates RNAs on genome.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121776181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identification of transcription hubs that control lipid metabolism and carbon concentrating mechanism in model microalgae chlamydomonas reinhardtii using regulatory networks: Regulatory networks hubs in C. reinhardtii that control lipid and carbon concentrating metabolic pathways 利用调控网络鉴定模型微藻莱茵衣藻控制脂质代谢和碳浓缩机制的转录枢纽:莱茵衣藻中控制脂质和碳浓缩代谢途径的调控网络枢纽

2016 International Conference on Bioinformatics and Systems Biology (BSB) Pub Date : 2016-03-04 DOI: 10.1109/BSB.2016.7552116

Rahila Sardar, K. Shaikh, P. P. Jutur

{"title":"Identification of transcription hubs that control lipid metabolism and carbon concentrating mechanism in model microalgae chlamydomonas reinhardtii using regulatory networks: Regulatory networks hubs in C. reinhardtii that control lipid and carbon concentrating metabolic pathways","authors":"Rahila Sardar, K. Shaikh, P. P. Jutur","doi":"10.1109/BSB.2016.7552116","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552116","url":null,"abstract":"Chlamydomonas reinhardtii is the most extensively studied eukaryotic model microalgae having essential biological pathways such as biomass production, photosynthesis, carbon concentrating mechanisms (CCMs), carbohydrate metabolism (CM), lipid metabolism (LM), and response towards nutritional stresses, with fine-tuned physiological data and genome sequence available publicly. During nitrogen (N) deprivation, C. reinhardtii accumulates oil (triacylglycerols, TAG) as storage reserves and studies to understand the entire global regulatory network is still not clear. Recent studies showed that they have identified and characterized entire set of genes encoding transcription factors (TFs) and transcriptional regulators (TRs)that control lipid metabolism relative to other genes under different stress responses using combined omics analysis but evaluation of common TFs and TRs under normal conditions involving LMand CCM in combination is essential for understanding regulatory network that may lead to identification of several regulatory hubs that controls these essential cellular processes. Our study will focus on reconstruction of a regulatory network from publicly available databases such as PlnTFDB, STRING and elucidate common TFs and TRs essential for both these mechanisms. We have identified new TFs and TRs such as, SET, PHD, FHA, Myb, Myb-related, and HMGthat play an important role in different functions such as control of chromatin and/or transcription, methylation of lysine residues, DNA repair, signal transduction etc. Also, our findings demonstrate that these TFs and TRs are involved in photoreceptor-like activities in the model microalga, which has the maximum degree of interactions with different genes and thus have relevant physiological importance in both these mechanisms.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126106291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

An account of Genomic Islands of zoonotic origin Staphylococcus aureus genomes — In silico approach 人畜共患源性金黄色葡萄球菌基因组基因组岛的记述-计算机方法

2016 International Conference on Bioinformatics and Systems Biology (BSB) Pub Date : 2016-03-04 DOI: 10.1109/BSB.2016.7552166

Relangi Tulasi Rao, Saghya Infant Shofia, A. Manna, K. Jayakumar

{"title":"An account of Genomic Islands of zoonotic origin Staphylococcus aureus genomes — In silico approach","authors":"Relangi Tulasi Rao, Saghya Infant Shofia, A. Manna, K. Jayakumar","doi":"10.1109/BSB.2016.7552166","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552166","url":null,"abstract":"Genomic Islands (GIs) are commonly believed to be relics of horizontal transfer and associated with specific metabolic capacities, including virulence of the strain. Staphylococcus aureus is a commensal, Gram-positive bacteria found in both animals and humans. Amid stress or immune compromised conditions of the host, the bacteria known to induce diseases. In this study, we predicted GIs, a relative dissection and portrayed significant virulence factors associated with GIs. The study recognized distinct regions of the GIs of S. aureus RF122 which imparted with the other strains. Many GIs of RF122 strain homologous to other strains and sharing common lineage. In spite of its small genome size RF122 strain harbours 18 GIs evident for rapid horizontal gene transfer events during its evolution. It has concluded from the mechanisms involved in gene transfer, phage infections and transposase are important mechanisms of the horizontal transfer in the study strains. Resistance Islands and Pathogenicity islands are common subtypes of predicted GIs of study genomes. Drug resistance and virulence of S. aureus enhanced because of GIs. Another important finding of this study is it also proved S. aureus adopted to host niche because of horizontally acquired GIs. Based on sequence similarity it suggests that ST398 strain has evolved recently. Further, GI Knockout studies needed for validation of role of GIs in transforming commensal to virulent strain.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129817082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

QSAR model development for solubility prediction of Paclitaxel 紫杉醇溶解度预测QSAR模型的建立

2016 International Conference on Bioinformatics and Systems Biology (BSB) Pub Date : 2016-03-04 DOI: 10.1109/BSB.2016.7552139

Nupur S. Munjal, Narendra Kumar, Manu Sharma, Chittaranjan Rout

引用次数: 0

In silico peptide based vaccine against hepatitis C virus 基于硅肽的丙型肝炎病毒疫苗

2016 International Conference on Bioinformatics and Systems Biology (BSB) Pub Date : 2016-03-04 DOI: 10.1109/BSB.2016.7552119

V. Kaushik, Joginder Singh, Nidhi Sharma

{"title":"In silico peptide based vaccine against hepatitis C virus","authors":"V. Kaushik, Joginder Singh, Nidhi Sharma","doi":"10.1109/BSB.2016.7552119","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552119","url":null,"abstract":"Hepatitis C is a severe disease caused by Hepatitis C virus which leads to human fatality and affected 180 million people across the globe. Its chronic infection leads to liver damage and malignant hepatoma. Till now there is no vaccine in the market for this virus. The objective of the study was to predict the best epitope using Bioinformatics tools for designing a vaccine against HCV. Here T-cell epitope was considered since it can recognize only antigen that processes to generate peptide by antigen presenting cell. For selecting the best T cell epitope, the binding energy with the MHC molecule must be high, must have a protease cleavage site, conserved site, motif, good binder with hydrophobic binding pocket and half-life of dissociation must be high. By considering above criteria suitable bioinformatics tools were used to predict the epitopes from NS3, NS5A and NS5B of 3a and 3b genotype. A total of 600 epitopes from different tools for each protein were predicted and from there only 11 efficient epitopes was virtually screened out using protein-protein interaction between MHC-I and MHC-II molecules and their energy. IMYAPTIWV peptide of NS5A protein was found to be the best epitope. The selected epitope for T-cell can further be used for future work in a wet laboratory for the development of vaccine against HCV.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126978734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

3D structure prediction and molecular dynamics simulation studies of GPR139 GPR139的三维结构预测及分子动力学模拟研究

2016 International Conference on Bioinformatics and Systems Biology (BSB) Pub Date : 2016-03-04 DOI: 10.1109/BSB.2016.7552143

A. Kaushik, S. Sahi

引用次数: 1

“Who are the key players behind a disease state?”: Outcomes of a new computational approach on cancer data “谁是疾病状态背后的关键人物?”:癌症数据新计算方法的结果

2016 International Conference on Bioinformatics and Systems Biology (BSB) Pub Date : 2016-03-04 DOI: 10.1109/BSB.2016.7552148

Jeethu V. Devasia, P. Chandran

{"title":"“Who are the key players behind a disease state?”: Outcomes of a new computational approach on cancer data","authors":"Jeethu V. Devasia, P. Chandran","doi":"10.1109/BSB.2016.7552148","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552148","url":null,"abstract":"The problem of identifying disease causing genes and dysregulated pathways has attained a key position in computational biology research, as it helps in understanding major causal genes and their interactions behind a disease state and thereby enables proposing new drug targets. The development of computational approaches for the inference of disease causing genes and associated pathways can improve the accuracy and efficiency and reduce the cost of biomedical analysis. Identification of disease causing genes from the large set of genes produced by high throughput experiments is a time consuming and costly process. Based on the fact that interactions among several genes results in certain phenotypes, the molecular interaction network is a major resource for computational approaches to identify disease causing genes and associated pathways. Executing computations on the huge molecular interaction network is also major challenge. Here, we address the problem of inferring disease causing genes and their pathways using graph theoretical approaches which focus on reducing the execution time by using graph pruning techniques, without compromising on accuracy of results. Experimentation on real biological data shows reduced execution time and increased accuracy than other methods reported in literature on benchmark datasets, on using the proposed technique.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"1993 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128629105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1