Pub Date : 2016-03-04DOI: 10.1109/BSB.2016.7552133
Gajendra Sharma, Manish Kumar, S. Verma
This paper provides a statistical method for detecting tree cutting activity using acoustic signals produced by saw scratching through a bole. An experimental setup is proposed for recording the data in real time environment. Data was collected and then processed by an SNR based algorithm to separate the noise from acoustic signals. A modified MFCC is then used to draw out the features of each five-second sample received after preprocessing. Linde-Buzo-Gray algorithm is used to fetch the statistical properties of the identified feature array. Finally, the acoustic signals are classified using Dynamic Time Warping (DTW) algorithm and half of the identified feature array and performance of the algorithm were tested by using rest of the marked feature arrays.
本文提供了一种统计方法来检测树木的砍伐活动，利用声音信号产生的锯划破一个孔。提出了一种在实时环境下记录数据的实验装置。采集数据后，采用基于信噪比的算法将噪声从声信号中分离出来。然后使用改进的MFCC来绘制预处理后接收到的每个5秒样本的特征。采用Linde-Buzo-Gray算法提取特征数组的统计属性。最后，采用动态时间翘曲(Dynamic Time Warping, DTW)算法对声信号进行分类，并对识别出的一半特征阵列和算法的性能进行测试。
{"title":"Monitoring deforestation using acoustic signals","authors":"Gajendra Sharma, Manish Kumar, S. Verma","doi":"10.1109/BSB.2016.7552133","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552133","url":null,"abstract":"This paper provides a statistical method for detecting tree cutting activity using acoustic signals produced by saw scratching through a bole. An experimental setup is proposed for recording the data in real time environment. Data was collected and then processed by an SNR based algorithm to separate the noise from acoustic signals. A modified MFCC is then used to draw out the features of each five-second sample received after preprocessing. Linde-Buzo-Gray algorithm is used to fetch the statistical properties of the identified feature array. Finally, the acoustic signals are classified using Dynamic Time Warping (DTW) algorithm and half of the identified feature array and performance of the algorithm were tested by using rest of the marked feature arrays.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"31 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":"130601280","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.2016.7552161
Akhil Kumar, Gaurava Srivastava, Ashok Sharma
Aβ generation and τ hyper-phosphorylation are the two major hallmarks for the neurodegenrative Alzheimer's disease. These two conditions arises due to the protease BACE-1 and kinase GSK-3β enzymes respectively. Multi target directed ligand is better strategy to fight with multifactorial disease like Alzheimer's disease. In this context recently a dual inhibitor is reported to inhibit these two crucial targets of Alzheimer's disease. There is need to discover novel more potent inhibitor against these two target. So with the help of computational method we tried to understand the important binding residues of both the target and conformation of dual inhibitor 1 in the active site. This computational study reveal the important residues responsible for dual binding further can be used to generated and predict new lead.
{"title":"In silico interaction studies of first dual inhibitor against BACE-1/GSK-3β","authors":"Akhil Kumar, Gaurava Srivastava, Ashok Sharma","doi":"10.1109/BSB.2016.7552161","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552161","url":null,"abstract":"Aβ generation and τ hyper-phosphorylation are the two major hallmarks for the neurodegenrative Alzheimer's disease. These two conditions arises due to the protease BACE-1 and kinase GSK-3β enzymes respectively. Multi target directed ligand is better strategy to fight with multifactorial disease like Alzheimer's disease. In this context recently a dual inhibitor is reported to inhibit these two crucial targets of Alzheimer's disease. There is need to discover novel more potent inhibitor against these two target. So with the help of computational method we tried to understand the important binding residues of both the target and conformation of dual inhibitor 1 in the active site. This computational study reveal the important residues responsible for dual binding further can be used to generated and predict new lead.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"30 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120907087","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.2016.7552153
Arnab Sadhu, B. Bhattacharyya
Gene expression data from microarray experiments offer enormous scope for exploring the genetic relationship of deadly diseases. The motivation is to explore possible molecular biomarkers of such diseases with a view to early and periodic detection. A study has been reported in this paper with a methodology for common subcluster mining using FCM clustering. Subcluster refers to the peak formed through superimposition of clusters obtained from expressional data, both from the normal and diseased samples separately. Experiments are carried out on datasets of lung cancer, Acute Myeloid Leukemia(AML) and breast cancer employing the algorithm for common subcluster mining. Results are found to match to a large extent with those obtained in previous studies. Few genes emerge as indicative molecular biomarkers of respective diseases.
{"title":"Discovery of cancer linked biomarker genes through common subcluster mining","authors":"Arnab Sadhu, B. Bhattacharyya","doi":"10.1109/BSB.2016.7552153","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552153","url":null,"abstract":"Gene expression data from microarray experiments offer enormous scope for exploring the genetic relationship of deadly diseases. The motivation is to explore possible molecular biomarkers of such diseases with a view to early and periodic detection. A study has been reported in this paper with a methodology for common subcluster mining using FCM clustering. Subcluster refers to the peak formed through superimposition of clusters obtained from expressional data, both from the normal and diseased samples separately. Experiments are carried out on datasets of lung cancer, Acute Myeloid Leukemia(AML) and breast cancer employing the algorithm for common subcluster mining. Results are found to match to a large extent with those obtained in previous studies. Few genes emerge as indicative molecular biomarkers of respective diseases.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"49 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":"116414710","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.2016.7552162
A. Sengupta, P. Narad
The developing method of network medicine offers a stage to investigate efficiently not only the molecular complexity of a certain disease but additionally recognizes the ailment modules and the interconnectivity of the pathways. Hyper and hypo glycemia are one of the major diseases faced today in the western world. The level of glucose in the blood is controlled by insulin and glucagon henceforth a homeostasis is maintained. To solve this problem we present a formulated hypothesis where the basis revolves around the central idea of energy conservation and the energy currencies in a cell. Further we reconstructed a Human Energy Pool Network (HEPNet) with 4 compartments, 173 metabolic reactions and 158 metabolites; analyzed and characterized from various resources under a range of conditions into a kinetic model backbone. Ordinary differential equations generated through the network inferred that the glucose concentration is dependent on several factors but varies as a logarithmic function. Time course simulations were carried out and flux balance analysis validated the findings that ATP flux is dependent on 7 reactions with glucose playing a major role referred to as the Glucose component which varies logarithmically in a flux based ordinary differential equation. This glucose component denotes the change of flux behavior in the hypoglycemic and hyperglycemic condition.
{"title":"Glucose concentration varies logarithmically under both glycemic conditions in a computationally reconstructed human energy pool network (HEPNet)","authors":"A. Sengupta, P. Narad","doi":"10.1109/BSB.2016.7552162","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552162","url":null,"abstract":"The developing method of network medicine offers a stage to investigate efficiently not only the molecular complexity of a certain disease but additionally recognizes the ailment modules and the interconnectivity of the pathways. Hyper and hypo glycemia are one of the major diseases faced today in the western world. The level of glucose in the blood is controlled by insulin and glucagon henceforth a homeostasis is maintained. To solve this problem we present a formulated hypothesis where the basis revolves around the central idea of energy conservation and the energy currencies in a cell. Further we reconstructed a Human Energy Pool Network (HEPNet) with 4 compartments, 173 metabolic reactions and 158 metabolites; analyzed and characterized from various resources under a range of conditions into a kinetic model backbone. Ordinary differential equations generated through the network inferred that the glucose concentration is dependent on several factors but varies as a logarithmic function. Time course simulations were carried out and flux balance analysis validated the findings that ATP flux is dependent on 7 reactions with glucose playing a major role referred to as the Glucose component which varies logarithmically in a flux based ordinary differential equation. This glucose component denotes the change of flux behavior in the hypoglycemic and hyperglycemic condition.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"469 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":"117009472","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.2016.7552164
S. Chatterjee, B. Sanjeev
While most studies emphasize on certain aspects of Pathogen-Host Interactions (PHI), such as the preferential attachment of bacteria or virus to its human receptor homolog, studies have attempted to methodically classify interactions among pathogenic proteins and their host proteins. Here we have analyzed 182 pathogens from The Pathogen-Host Interaction Search Tool (PHISTO) [1] and could identify the proteins/protein coding genes that act on both virus and bacteria. Importantly there were few proteins viz. P53 (Tumor protein p53), NFKB1 (Nuclear factor of kappa light polypeptide gene enhancer in B-cells 1), GBLP (Guanine nucleotide-binding protein subunit beta-2-like-1), TOX4 (TOX high mobility group box family member 4), PDIA1 (Protein disulfide-isomerase precursor), MHY9 (Myosin 9), RAC1 (Ras-related C3 botulinum toxin substrate 1), CCAR2 (Cell cycle and apoptosis regulator protein 2) and ILF3 (Interleukin enhancer binding factor 3) that were more susceptible to both bacterial and viral pathogens. Identification of such important interacting proteins (IIPs) can elicit significant insights for better understanding the molecular mechanisms of such pathogens that interact with the human host.
{"title":"Identification of human proteins vulnerable to multiple organisms","authors":"S. Chatterjee, B. Sanjeev","doi":"10.1109/BSB.2016.7552164","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552164","url":null,"abstract":"While most studies emphasize on certain aspects of Pathogen-Host Interactions (PHI), such as the preferential attachment of bacteria or virus to its human receptor homolog, studies have attempted to methodically classify interactions among pathogenic proteins and their host proteins. Here we have analyzed 182 pathogens from The Pathogen-Host Interaction Search Tool (PHISTO) [1] and could identify the proteins/protein coding genes that act on both virus and bacteria. Importantly there were few proteins viz. P53 (Tumor protein p53), NFKB1 (Nuclear factor of kappa light polypeptide gene enhancer in B-cells 1), GBLP (Guanine nucleotide-binding protein subunit beta-2-like-1), TOX4 (TOX high mobility group box family member 4), PDIA1 (Protein disulfide-isomerase precursor), MHY9 (Myosin 9), RAC1 (Ras-related C3 botulinum toxin substrate 1), CCAR2 (Cell cycle and apoptosis regulator protein 2) and ILF3 (Interleukin enhancer binding factor 3) that were more susceptible to both bacterial and viral pathogens. Identification of such important interacting proteins (IIPs) can elicit significant insights for better understanding the molecular mechanisms of such pathogens that interact with the human host.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"27 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":"127975381","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.2016.7552158
N. Rai, D. Mishra, Sanjeev Kumar, A. Rai, K. K. Chaturvedi, S. B. Lal, Anil Kumar, M. Farooqi, P. G. Majumdar, S. Archak
Bacteria from genus Rhizobium have ability to fix atmospheric nitrogen in symbiosis with leguminous plants resulting in formation of root nodules. They act as an alternate source of nitrogenous fertilizers. The study of codon usage patterns of Rhizobium species is gaining increasing attention over the times. In the present study three strains of Rhizobium namely Sinorhizobium meliloti 1021, Bradyrhizobium japonicum USDA110 and Rhizobium tropici CIAT899 whose complete genome sequence are available were retrieved from NCBI for the analysis of codon usage. The overall codon usage analysis showed that codons ending with G and C are preferred more in the rhizobium genome than codon ending with A and T. ENc plot revealed that compositional constraints along with translational selection are the major cause of codon usage bias. Correspondence analysis (COA) showed that the variation in codon usage is accounted mainly by the first two axes. From the Pearson correlation analysis significant correlation was identified among the first axis of COA and Codon adaptation index (CAI) and other factors of codon usage bias. 17 optimal codons were identified that were shared among these three strains.
{"title":"Genome analysis of Rhizobium species using codon usage bias tools","authors":"N. Rai, D. Mishra, Sanjeev Kumar, A. Rai, K. K. Chaturvedi, S. B. Lal, Anil Kumar, M. Farooqi, P. G. Majumdar, S. Archak","doi":"10.1109/BSB.2016.7552158","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552158","url":null,"abstract":"Bacteria from genus Rhizobium have ability to fix atmospheric nitrogen in symbiosis with leguminous plants resulting in formation of root nodules. They act as an alternate source of nitrogenous fertilizers. The study of codon usage patterns of Rhizobium species is gaining increasing attention over the times. In the present study three strains of Rhizobium namely Sinorhizobium meliloti 1021, Bradyrhizobium japonicum USDA110 and Rhizobium tropici CIAT899 whose complete genome sequence are available were retrieved from NCBI for the analysis of codon usage. The overall codon usage analysis showed that codons ending with G and C are preferred more in the rhizobium genome than codon ending with A and T. ENc plot revealed that compositional constraints along with translational selection are the major cause of codon usage bias. Correspondence analysis (COA) showed that the variation in codon usage is accounted mainly by the first two axes. From the Pearson correlation analysis significant correlation was identified among the first axis of COA and Codon adaptation index (CAI) and other factors of codon usage bias. 17 optimal codons were identified that were shared among these three strains.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"24 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":"131626736","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.2016.7552145
R. Tripathi, Pawan Sharma, P. Chakraborty, P. Varadwaj
Phytophthora infestans (Mont.) de Bary, oomycetes model organism is a destructive pathogen having a broad host range within Solanaceae family resulting in devastating economic losses every year. It causes late blight of Solanum tuberosum (potato) and S. lycopersicum (tomato). Current studies of the host-pathogen system emphasize on gene expression pattern of the Solanaceae members neglecting pathogen gene expression. In this paper the molecular properties of virulent proteins were investigated and classified on the basis of their functional, biophysical and biochemical properties. Bio-computational investigations and statistical analysis of the protein sequences was done. IpiO (ACU56995.1) one of the known virulent protein responsible for the disease, showed its similarity with HSF-type DNA-binding (EEY62722.1) non-virulent protein. Molecular modeling of the non-virulent protein was done. Modeled structure provided substantial parameters under Ramachandran plot, stereo-chemical aspects of the model was evaluated using RAMPAGE web server. Comparative genomic approach, and at a more basic level characterizations of P. infestans virulent proteins as well as understanding the perturbations they facilitate in plants will greatly enhance one's understanding of P. infestans virulence and host specificity.
卵霉菌模式生物——疫霉(Phytophthora infestans (Mont.) de Bary)是茄科中具有广泛寄主范围的破坏性病原体，每年造成毁灭性的经济损失。它引起马铃薯和番茄的晚疫病。目前对茄科植物宿主-病原菌系统的研究主要集中在茄科植物的基因表达模式上，而忽视了病原菌的基因表达。本文根据毒力蛋白的功能、生物物理和生化特性，对毒力蛋白的分子特性进行了研究和分类。对蛋白质序列进行了生物计算研究和统计分析。IpiO (ACU56995.1)是已知引起该病的毒力蛋白之一，与hsf型dna结合蛋白(EEY62722.1)无毒蛋白具有相似性。对无毒蛋白进行了分子模拟。模型结构在Ramachandran图下提供了大量参数，模型的立体化学方面使用RAMPAGE web服务器进行评估。比较基因组学方法，在更基本的水平上表征病原菌毒力蛋白，以及了解它们在植物中促进的扰动，将极大地提高人们对病原菌毒力和宿主特异性的理解。
{"title":"In silico identification of novel virulent protein of phytophthora infestans related to late blight disease","authors":"R. Tripathi, Pawan Sharma, P. Chakraborty, P. Varadwaj","doi":"10.1109/BSB.2016.7552145","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552145","url":null,"abstract":"Phytophthora infestans (Mont.) de Bary, oomycetes model organism is a destructive pathogen having a broad host range within Solanaceae family resulting in devastating economic losses every year. It causes late blight of Solanum tuberosum (potato) and S. lycopersicum (tomato). Current studies of the host-pathogen system emphasize on gene expression pattern of the Solanaceae members neglecting pathogen gene expression. In this paper the molecular properties of virulent proteins were investigated and classified on the basis of their functional, biophysical and biochemical properties. Bio-computational investigations and statistical analysis of the protein sequences was done. IpiO (ACU56995.1) one of the known virulent protein responsible for the disease, showed its similarity with HSF-type DNA-binding (EEY62722.1) non-virulent protein. Molecular modeling of the non-virulent protein was done. Modeled structure provided substantial parameters under Ramachandran plot, stereo-chemical aspects of the model was evaluated using RAMPAGE web server. Comparative genomic approach, and at a more basic level characterizations of P. infestans virulent proteins as well as understanding the perturbations they facilitate in plants will greatly enhance one's understanding of P. infestans virulence and host specificity.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"2 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":"134572883","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.2016.7552129
Ayon Pal, A. K. Bothra, U. Mandal, Subhasis Mukhopadhyay
Multidrug defiant organisms result in severe mortality and stand as a big challenge worldwide. The gram negative bacilli (GNB) in particular is a massive cause of concern with high levels of resistance due to novel mechanisms. This study deals with thorough analysis of the phylogeny, evolutionary divergence and protein tertiary structure analysis of an important drug target, the bacterial metallo-amidase enzyme LpxC. The LpxC enzyme exists universally in all the gram-negative bacteria and catalyzes the first committed step of Lipid A biosynthesis. Evolutionary divergence study revealed the lpxC gene to be under strong degree of purifying selection in many highly pathogenic bacterial species. Homology modeling of the LpxC enzyme from different human pathogenic bacteria was carried out along with critical model evaluation and structural alignment analysis. Investigation of clefts on the LpxC protein surface demonstrated the presence of specific residues within the substrate-binding cleft. Preference for different secondary structural elements within the major cleft was also noticed in the LpxC enzyme from the sixteen selected pathogenic bacterial species.
{"title":"Evolutionary divergence and comparative homology modeling analysis of LpxC enzyme from human pathogenic bacteria","authors":"Ayon Pal, A. K. Bothra, U. Mandal, Subhasis Mukhopadhyay","doi":"10.1109/BSB.2016.7552129","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552129","url":null,"abstract":"Multidrug defiant organisms result in severe mortality and stand as a big challenge worldwide. The gram negative bacilli (GNB) in particular is a massive cause of concern with high levels of resistance due to novel mechanisms. This study deals with thorough analysis of the phylogeny, evolutionary divergence and protein tertiary structure analysis of an important drug target, the bacterial metallo-amidase enzyme LpxC. The LpxC enzyme exists universally in all the gram-negative bacteria and catalyzes the first committed step of Lipid A biosynthesis. Evolutionary divergence study revealed the lpxC gene to be under strong degree of purifying selection in many highly pathogenic bacterial species. Homology modeling of the LpxC enzyme from different human pathogenic bacteria was carried out along with critical model evaluation and structural alignment analysis. Investigation of clefts on the LpxC protein surface demonstrated the presence of specific residues within the substrate-binding cleft. Preference for different secondary structural elements within the major cleft was also noticed in the LpxC enzyme from the sixteen selected pathogenic bacterial species.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"13 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":"132668398","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.2016.7552118
Sonal Mishra, K. Misra
The common human pathogenic fungus, Candida albicans has gained importance for its role in creating animbalance in the human biome. The majority of metabolic diseases have been caused by epigenetic changes in the bacterial and fungal species inhabiting inside the biome. Also the fungal infections had further aggravated the conditions in immunocompromised people. In the present study the factors contributing to the pathogenicity in C albicans have been highlighted and the combination of transcriptional factors Tec1 and Rfg1 have been targeted. These factors work linearly to induce hypha growth in albicans which brews virulence. We have designed a common ligand which can bind effectively with both factors thus inhibiting the serious fungal infections and damages caused by these.
{"title":"In-silico based designing of inhibitors against thevirulence and filamentation of Candida albicans, a common human pathogen","authors":"Sonal Mishra, K. Misra","doi":"10.1109/BSB.2016.7552118","DOIUrl":"https://doi.org/10.1109/BSB.2016.7552118","url":null,"abstract":"The common human pathogenic fungus, Candida albicans has gained importance for its role in creating animbalance in the human biome. The majority of metabolic diseases have been caused by epigenetic changes in the bacterial and fungal species inhabiting inside the biome. Also the fungal infections had further aggravated the conditions in immunocompromised people. In the present study the factors contributing to the pathogenicity in C albicans have been highlighted and the combination of transcriptional factors Tec1 and Rfg1 have been targeted. These factors work linearly to induce hypha growth in albicans which brews virulence. We have designed a common ligand which can bind effectively with both factors thus inhibiting the serious fungal infections and damages caused by these.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"53 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":"122175985","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.2016.7552144
Archana Singh, Mahendra Gaur, E. Subudhi
Deciphering the microbial diversity of the Deulajhari thermal springs is the major goal of our study. In our study the taxonomic description of the bacterial community structure was deduced from the 1.52 Gb metagenomics sequence size from the Deulajhari hot spring located in the Angul district of Odisha. Covered with the dense foliage, it has a high temperature, i.e. 69°C and alkaline pH i.e. 8.09. Various physiochemical parameter analysis of the sediment like; electro conductivity (0.025dSm-1), total organic carbon content (0.356%), nitrogen (125 kg/ha), phosphorus (7.88 kg/ha) and potassium (169.34 kg/ha) were done. Sediment sample of the Deulajhari hot spring was further processed for the 16S rRNA V3-V4 region by the amplicon metagenome sequencing from community DNA. Approximately 88.12% of the total microbial diversity was represented by the Proteobacteria followed by Bacteroidetes 10.76%, Firmicutes 0.35%, Spirochetes 0.18%, Thermi 0.13% and chloroflexi 0.11% at the phylum level. Thus through the metagenomics sequencing of the Deulajhari hot spring using IIllumina platform, we represent the complete microbial community structure present there in respective of their allocation, profusion and diverse coexisting microbiota.
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