Pub Date : 2016-08-25DOI: 10.1109/BSB.2016.7552124
Kalpana Singh, Manish Kumar, Sekhar Verma
Most of the agronomically important traits are quantitative and found to be correlated to each other. These correlated quantitative traits are important to develop high yielding and resistant varieties of various economically important crops to combat the needs of increasing population. This paper work utilized data mining approach to extract patterns/rulesfrom quantitative trait locus database to find associated traits of 10 important crops. In comparison with traditional approaches, this study provides a simple and fast approach for finding associated quantitative traits.
{"title":"Extraction of associated quantitative traits by association mining","authors":"Kalpana Singh, Manish Kumar, Sekhar Verma","doi":"10.1109/BSB.2016.7552124","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552124","url":null,"abstract":"Most of the agronomically important traits are quantitative and found to be correlated to each other. These correlated quantitative traits are important to develop high yielding and resistant varieties of various economically important crops to combat the needs of increasing population. This paper work utilized data mining approach to extract patterns/rulesfrom quantitative trait locus database to find associated traits of 10 important crops. In comparison with traditional approaches, this study provides a simple and fast approach for finding associated quantitative traits.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131777518","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}
Pub Date : 2016-08-25DOI: 10.1109/BSB.2016.7552131
Imlimaong Aier, Utkarsh Raj
Polycomb group (PcG) proteins have been observed to maintain the pattern of histone by methylation of the histone tail responsible for the gene expression in various cellular processes. The PcG protein consists of two multicomplex, Polycomb Repressive Complexes 1 and 2, which includes Enhancer of zeste homolog 2 (EZH2) acting so that the histones silences tumor suppressor genes. Overexpression of EZH2 results in hyper activation observed in various forms of cancer, for instance, prostate and breast cancer. In the past decade, potent inhibitors for EZH2 have been discovered. However, reports of natural compounds for targeting EZH2 is significantly less. The druglikeness and pharmacokinetic properties of several natural compounds were analyzed and the compound with top inhibitory property was studied by molecular docking. A GLIDE score of -8.223 kcal/mol with stable interaction between the protein and ligand was observed for a simulation of 50 ns. This suggests the use of selected compound as an effective inhibitor for EZH2.
Polycomb group (PcG)蛋白通过在各种细胞过程中负责基因表达的组蛋白尾部甲基化来维持组蛋白的模式。PcG蛋白由两个多复合物组成，多梳抑制复合物1和2，其中包括zeste同源增强子2 (EZH2)，其作用是使组蛋白沉默肿瘤抑制基因。EZH2的过表达导致多种癌症的过度激活，例如前列腺癌和乳腺癌。在过去的十年中，已经发现了EZH2的有效抑制剂。然而，针对EZH2的天然化合物的报道却少得多。分析了几种天然化合物的药物相似性和药动学性质，并通过分子对接研究了具有顶级抑制性能的化合物。在50 ns的模拟时间内，该蛋白与配体的相互作用稳定，GLIDE分数为-8.223 kcal/mol。这表明使用选定的化合物作为EZH2的有效抑制剂。
{"title":"Exploring the role of EZH2 (PRC2) as epigenetic target","authors":"Imlimaong Aier, Utkarsh Raj","doi":"10.1109/BSB.2016.7552131","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552131","url":null,"abstract":"Polycomb group (PcG) proteins have been observed to maintain the pattern of histone by methylation of the histone tail responsible for the gene expression in various cellular processes. The PcG protein consists of two multicomplex, Polycomb Repressive Complexes 1 and 2, which includes Enhancer of zeste homolog 2 (EZH2) acting so that the histones silences tumor suppressor genes. Overexpression of EZH2 results in hyper activation observed in various forms of cancer, for instance, prostate and breast cancer. In the past decade, potent inhibitors for EZH2 have been discovered. However, reports of natural compounds for targeting EZH2 is significantly less. The druglikeness and pharmacokinetic properties of several natural compounds were analyzed and the compound with top inhibitory property was studied by molecular docking. A GLIDE score of -8.223 kcal/mol with stable interaction between the protein and ligand was observed for a simulation of 50 ns. This suggests the use of selected compound as an effective inhibitor for EZH2.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"496 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132480310","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}
In this study, we present a method for the catalytic site prediction of proteins rest on the triads of amino acids residues using non parametric function - artificial neural network. Using this method, we can efficiently predict that whether the amino acid triads of a protein are the part of catalytic site or not. For the preparation of training and test datasets, catalytic site residues of protein are downloaded from the database of catalytic site atlas and residues for non catalytic site are taken which are not participating in the formation of catalytic site of protein. This method used the numerical value of six physiochemical properties of amino acids along with the difference between centers of mass of whole protein and amino acids triads as the input for the neural network. Our analysis shows that this method is worked with the efficiency of 83.66% which is higher than other existing model for the prediction of catalytic site of protein. Our analysis is based on the residues physiochemical and topological properties and not on the evolutionary and sequence similarities so, In future, this work may help the researchers to develop tool and predicting the nature of residues of catalytic or active site of protein and may be helpful in ligand designing and molecular docking.
{"title":"Prediction of catalytic site of proteins based on amino acid triads approach using non parametric function","authors":"S. Srivastava, Gautam Kumar, Tapobarata Lahiri, Rajnish Kumar, Manoj Kumar Pal, Pragya Gupta, Rahul Gupta","doi":"10.1109/BSB.2016.7552137","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552137","url":null,"abstract":"In this study, we present a method for the catalytic site prediction of proteins rest on the triads of amino acids residues using non parametric function - artificial neural network. Using this method, we can efficiently predict that whether the amino acid triads of a protein are the part of catalytic site or not. For the preparation of training and test datasets, catalytic site residues of protein are downloaded from the database of catalytic site atlas and residues for non catalytic site are taken which are not participating in the formation of catalytic site of protein. This method used the numerical value of six physiochemical properties of amino acids along with the difference between centers of mass of whole protein and amino acids triads as the input for the neural network. Our analysis shows that this method is worked with the efficiency of 83.66% which is higher than other existing model for the prediction of catalytic site of protein. Our analysis is based on the residues physiochemical and topological properties and not on the evolutionary and sequence similarities so, In future, this work may help the researchers to develop tool and predicting the nature of residues of catalytic or active site of protein and may be helpful in ligand designing and molecular docking.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132141307","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}
Pub Date : 2016-08-25DOI: 10.1109/BSB.2016.7552128
Pankaj Kumar Singh, Jayita Roy, S. Ganguli, P. Basu, V. Vishal, Abhisek Ranjan Bera, Abhaydeep Pandey, R. Banik
Discovering and characterizing regulatory elements of miRNA genes are fundamental problems in bioinformatics field. An upstream regulatory motif can be described as a sequence element designated for binding of various protein factors imparting their subsequent effects on the transcription of the genes. For example, the transcription factors often bind to cis-acting conserved motif to regulate transcription, which typically are located upstream of transcriptional start sites. This work focuses on the identification of upstream regulatory elements of human microRNA genes by screening of their Kullback Liebler distance.
{"title":"Identification of conserved regulatory motif signatures in human miRNA upstream regions","authors":"Pankaj Kumar Singh, Jayita Roy, S. Ganguli, P. Basu, V. Vishal, Abhisek Ranjan Bera, Abhaydeep Pandey, R. Banik","doi":"10.1109/BSB.2016.7552128","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552128","url":null,"abstract":"Discovering and characterizing regulatory elements of miRNA genes are fundamental problems in bioinformatics field. An upstream regulatory motif can be described as a sequence element designated for binding of various protein factors imparting their subsequent effects on the transcription of the genes. For example, the transcription factors often bind to cis-acting conserved motif to regulate transcription, which typically are located upstream of transcriptional start sites. This work focuses on the identification of upstream regulatory elements of human microRNA genes by screening of their Kullback Liebler distance.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126479975","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}
The machine learning approaches frequently address the extraction of training datasets from the online databases to build computational or mathematical models. The training data downloaded from the online server and databases are most often carry redundancy and noise. Heuristics methods are most common to filter the data. Dataset filtering process is time consuming and researcher has to do this tedious work. We propose a more generic filter to detect frequent exceptions to increase the quality of generated datasets based on Perl Hash Programming and regular expression methodology. Future development of noise and error reduction approaches is important to make use of the full potential of available database knowledge. We make use of the datasets of protein - protein interaction generated by The University of Kansas Proteomics Service (KUPS).
{"title":"Improving extraction of protein — Protein interaction datasets from KUPS using hashing approach","authors":"Gautam Kumar, Rajnish Kumar, Manoj Kumar Pal, Pragya Gupta, Rahul Gupta, S. Mehra","doi":"10.1109/BSB.2016.7552135","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552135","url":null,"abstract":"The machine learning approaches frequently address the extraction of training datasets from the online databases to build computational or mathematical models. The training data downloaded from the online server and databases are most often carry redundancy and noise. Heuristics methods are most common to filter the data. Dataset filtering process is time consuming and researcher has to do this tedious work. We propose a more generic filter to detect frequent exceptions to increase the quality of generated datasets based on Perl Hash Programming and regular expression methodology. Future development of noise and error reduction approaches is important to make use of the full potential of available database knowledge. We make use of the datasets of protein - protein interaction generated by The University of Kansas Proteomics Service (KUPS).","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130066461","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}
Pub Date : 2016-08-25DOI: 10.1109/BSB.2016.7552136
Gautam Kumar, Tapobarata Lahiri, Rajnish Kumar
Recently published literatures indicate that, a consistent and precise classification system of microarray data is very essential for the successful identification of genes responsible for a cancer subtype and early treatment of cancer. However, in common clinical practice, diagnostic assertion of malignancies mostly relies on the morphological examination of tissues and clinical tests. In spite of the recent progress of treatment that uses semiempirical approaches involving computation methods, there are still uncertainties in cancer identification and diagnosis. High density oligonucleotide chips and genomic microarray data are being used progressively more in cancer research by generating huge expression data for thousands of genes simultaneously that poses problem of mining specific genes responsible for characterization of a specific cancer subtype. In this backdrop, we briefly address the impact of various statistical methods and their relative performances for the identification of potential probes and Discriminant genes for the breast cancer. We used Fisher's Discriminant Ratio (FDR), two tailed T-Test and vector norm on raw expression data and for each of the probe generated from the difference data accounting for up and down regulation of expression for each probes for various samples. The result indicates the potential of these methods to identify genes responsible for manifestation of breast cancer which is also well supported by the published result of experiments. The success of this approach not only gives the benefit of identification of cancer specific genes but also may help building of efficient classifier on the basis of these genes for automatic diagnostics of cancer.
最近发表的文献表明，一个一致和精确的微阵列数据分类系统对于成功识别癌症亚型的基因和癌症的早期治疗至关重要。然而，在常见的临床实践中，恶性肿瘤的诊断断言大多依赖于组织形态学检查和临床试验。尽管近年来使用涉及计算方法的半经验方法的治疗取得了进展，但在癌症的识别和诊断中仍然存在不确定性。高密度寡核苷酸芯片和基因组微阵列数据正在越来越多地用于癌症研究，同时产生数千个基因的大量表达数据，这给挖掘特定癌症亚型特征的特定基因带来了问题。在此背景下，我们简要地讨论了各种统计方法及其相对性能对乳腺癌潜在探针和判别基因鉴定的影响。我们使用Fisher’s Discriminant Ratio (FDR)、双尾t检验和矢量范数对原始表达数据和从差异数据生成的每个探针进行分析，以解释不同样本中每个探针的表达上下调节。这一结果表明，这些方法有潜力识别出与乳腺癌表现有关的基因，这也得到了已发表的实验结果的很好支持。该方法的成功不仅有利于癌症特异性基因的识别，而且有助于在这些基因的基础上建立有效的分类器，用于癌症的自动诊断。
{"title":"Statistical discrimination of breast cancer microarray data","authors":"Gautam Kumar, Tapobarata Lahiri, Rajnish Kumar","doi":"10.1109/BSB.2016.7552136","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552136","url":null,"abstract":"Recently published literatures indicate that, a consistent and precise classification system of microarray data is very essential for the successful identification of genes responsible for a cancer subtype and early treatment of cancer. However, in common clinical practice, diagnostic assertion of malignancies mostly relies on the morphological examination of tissues and clinical tests. In spite of the recent progress of treatment that uses semiempirical approaches involving computation methods, there are still uncertainties in cancer identification and diagnosis. High density oligonucleotide chips and genomic microarray data are being used progressively more in cancer research by generating huge expression data for thousands of genes simultaneously that poses problem of mining specific genes responsible for characterization of a specific cancer subtype. In this backdrop, we briefly address the impact of various statistical methods and their relative performances for the identification of potential probes and Discriminant genes for the breast cancer. We used Fisher's Discriminant Ratio (FDR), two tailed T-Test and vector norm on raw expression data and for each of the probe generated from the difference data accounting for up and down regulation of expression for each probes for various samples. The result indicates the potential of these methods to identify genes responsible for manifestation of breast cancer which is also well supported by the published result of experiments. The success of this approach not only gives the benefit of identification of cancer specific genes but also may help building of efficient classifier on the basis of these genes for automatic diagnostics of cancer.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"157 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114148644","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}
Pub Date : 2016-03-04DOI: 10.1109/BSB.2016.7552123
B. Pandey, Saurabh Gupta, Atmakuri Ramakrishna Rao, D. M. Pandey, R. Chatrath
An ubiquitous molecular chaperon, small heat shock proteins (sHSP) maintain protein homeostasis under stress conditions. Single nucleotide polymorphism was predicted in HSP16.9B gene but so far its impact on protein structure has not been extensively studied. Keeping this point in mind, we applied computational methods and performed molecular dynamics simulation to examine the effect of aspartic acid substitution for asparagine at 11th position (D11N) in HSP16.9B. Furthermore, the secondary structural analysis revealed an addition of beta sheet before the mutation point in the mutant protein. Three dimensional protein structure modeling, validation of structures and molecular dynamics were performed to study the mechanism of the non-synonymous single nucleotide polymorphism on structural changes. The root mean square deviation (RMSD) result showed the stability of the mutated structure throughout simulations. Moreover, root mean square fluctuation (RMSF) of atoms and Hydrogen-bond patterns further supported our results.
{"title":"Molecular modeling and dynamics study of nonsynonymous SNP in bread wheat HSP16.9B gene","authors":"B. Pandey, Saurabh Gupta, Atmakuri Ramakrishna Rao, D. M. Pandey, R. Chatrath","doi":"10.1109/BSB.2016.7552123","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552123","url":null,"abstract":"An ubiquitous molecular chaperon, small heat shock proteins (sHSP) maintain protein homeostasis under stress conditions. Single nucleotide polymorphism was predicted in HSP16.9B gene but so far its impact on protein structure has not been extensively studied. Keeping this point in mind, we applied computational methods and performed molecular dynamics simulation to examine the effect of aspartic acid substitution for asparagine at 11th position (D11N) in HSP16.9B. Furthermore, the secondary structural analysis revealed an addition of beta sheet before the mutation point in the mutant protein. Three dimensional protein structure modeling, validation of structures and molecular dynamics were performed to study the mechanism of the non-synonymous single nucleotide polymorphism on structural changes. The root mean square deviation (RMSD) result showed the stability of the mutated structure throughout simulations. Moreover, root mean square fluctuation (RMSF) of atoms and Hydrogen-bond patterns further supported our results.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"67 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":"115308632","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}
Pub Date : 2016-03-04DOI: 10.1109/BSB.2016.7552140
S. Ojha, Kanika Kundu, S. Kundu
Due to increase in the incidences of drug resistant pathogens, there is a need for the development of alternative drugs against which the microorganisms will not be able to develop resistance. The most promising candidates to be developed as alternative drugs are the antimicrobial peptides. In the present study the antimicrobial peptide Microcin C7 was docked with the catalytic domain of Diphtheria toxin and further the simulational studies were performed to find the stability of the complex. The results were significant and hence it was predicted that further work can be done on antimicrobial peptide to develop it as an alternative drug against Diphtheria toxin.
{"title":"Antimicrobial peptide Microcin C7 as an alternative drug candidate against Diphtheria toxin","authors":"S. Ojha, Kanika Kundu, S. Kundu","doi":"10.1109/BSB.2016.7552140","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552140","url":null,"abstract":"Due to increase in the incidences of drug resistant pathogens, there is a need for the development of alternative drugs against which the microorganisms will not be able to develop resistance. The most promising candidates to be developed as alternative drugs are the antimicrobial peptides. In the present study the antimicrobial peptide Microcin C7 was docked with the catalytic domain of Diphtheria toxin and further the simulational studies were performed to find the stability of the complex. The results were significant and hence it was predicted that further work can be done on antimicrobial peptide to develop it as an alternative drug against Diphtheria toxin.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"10 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":"127946874","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}
Pub Date : 2016-03-04DOI: 10.1109/BSB.2016.7552159
Sarika Sahu, A. Rao, K. C. Bansal, S. Muthusamy, V. Chinnusamy
Transcription factors (TFs) act as master regulators that directly bind to their respective distinct cis-regulatory elements and activate the expression of many downstream target genes (regulon), and thus play a key regulatory role in plant development and stress tolerance. TF families such as AP2/EREBP, AREB/ABF, bHLH, bZIP, C2H2, C3HIS, HB, DREB1/CBF, HSF, MADS, MYB, MYC, NAC, WRKY, etc., were known to regulate stress responses of plants and were relatively well studied in rice and Arabidopsis. Bread wheat (Triticumaestivum L) draft genome is recently released and is available in Ensembl Plants database. We used known rice TFs and build Hidden Markov Model (HMM) profiles for individual TF protein families. These Profile HMMs in turn were used to search respective wheat homologs. SMART tool was used for domain identification. Our analysis showed that the wheat genome consists of 201, 166, 265, 182, 200, 102, 200, 274, 54, 125, 315, 226 and 199 genes of AP2/EREBP, AREB/ABF, bHLH, bZIP, C2H2, C3HIS, HB, HIS, HSF, MADS, MYB, NAC and WRKY families, respectively. Genome-wide analysis of miRNAs from wheat genome resulted in identification of 4533 miRNAs from wheat. Further, miRNAs targeting abiotic stress responsive TFs is identified. The genome distribution of abiotic stress responsive TFs and miRNAs strongly supports the hypothesis that genome-wide and tandem duplication contributed to the expansion of these gene families in wheat.
{"title":"Genome-wide analysis and identification of abiotic stress responsive transcription factor family genes and miRNAs in bread wheat (Triticumaestivum L.): Genomic study of bread wheat","authors":"Sarika Sahu, A. Rao, K. C. Bansal, S. Muthusamy, V. Chinnusamy","doi":"10.1109/BSB.2016.7552159","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552159","url":null,"abstract":"Transcription factors (TFs) act as master regulators that directly bind to their respective distinct cis-regulatory elements and activate the expression of many downstream target genes (regulon), and thus play a key regulatory role in plant development and stress tolerance. TF families such as AP2/EREBP, AREB/ABF, bHLH, bZIP, C2H2, C3HIS, HB, DREB1/CBF, HSF, MADS, MYB, MYC, NAC, WRKY, etc., were known to regulate stress responses of plants and were relatively well studied in rice and Arabidopsis. Bread wheat (Triticumaestivum L) draft genome is recently released and is available in Ensembl Plants database. We used known rice TFs and build Hidden Markov Model (HMM) profiles for individual TF protein families. These Profile HMMs in turn were used to search respective wheat homologs. SMART tool was used for domain identification. Our analysis showed that the wheat genome consists of 201, 166, 265, 182, 200, 102, 200, 274, 54, 125, 315, 226 and 199 genes of AP2/EREBP, AREB/ABF, bHLH, bZIP, C2H2, C3HIS, HB, HIS, HSF, MADS, MYB, NAC and WRKY families, respectively. Genome-wide analysis of miRNAs from wheat genome resulted in identification of 4533 miRNAs from wheat. Further, miRNAs targeting abiotic stress responsive TFs is identified. The genome distribution of abiotic stress responsive TFs and miRNAs strongly supports the hypothesis that genome-wide and tandem duplication contributed to the expansion of these gene families in wheat.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"72 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":"127135957","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}
Pub Date : 2016-03-04DOI: 10.1109/BSB.2016.7552156
D. Mishra, S. Mittal, I. Singh, Sanjeev Kumar, A. Rai
Co-regulated genes are important for better understanding of how multiple genes are affected in an organism under abiotic stress. In this study, co-regulated genes of chick pea identified. Formulation of clusters of co-expressed genes for each stress has been done by consensus clustering technique and interconnected pathway has been identified using Kyoto Encyclopedia of Genes and Genomes (KEGG) server.
{"title":"Identification of co-regulated genes of chick pea under abiotic stress","authors":"D. Mishra, S. Mittal, I. Singh, Sanjeev Kumar, A. Rai","doi":"10.1109/BSB.2016.7552156","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552156","url":null,"abstract":"Co-regulated genes are important for better understanding of how multiple genes are affected in an organism under abiotic stress. In this study, co-regulated genes of chick pea identified. Formulation of clusters of co-expressed genes for each stress has been done by consensus clustering technique and interconnected pathway has been identified using Kyoto Encyclopedia of Genes and Genomes (KEGG) server.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"27 10 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":"123244328","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}
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