Vidya V. Iyer, I. Androulakis, C. M. Roth, M. Ierapetritou
{"title":"Effects of Triadimefon on the Metabolism of Cultured Hepatocytes","authors":"Vidya V. Iyer, I. Androulakis, C. M. Roth, M. Ierapetritou","doi":"10.1109/BIBE.2010.28","DOIUrl":"https://doi.org/10.1109/BIBE.2010.28","url":null,"abstract":"The liver, being the major site of metabolism, plays a critical role in xenobiotic biotransformation and clearance. Quantifying the links between central hepatic and xenobiotic metabolism is critical to understanding toxicant-induced hepatic injury. Conazoles are a class of azole fungicides used to prevent fungal growth in fruits, vegetables and seeds, and for the treatment of fungal infections. Certain conazoles (such as triadimefon) are found to be tumorigenic in rats and mice. In this study, cultured primary rat hepatocytes were treated to varying doses (less than or equal to 0.3 mM) of triadimefon on a temporal basis with daily media change. Following exposure, supernatant was collected daily for 3 days and concentration of various metabolites (triadimefon, glucose, urea, albumin, amino acids, fatty acids, cholesterol etc.) in the media and supernatant were quantified. Albumin production was reduced in 0.3 mM triadimefon treated cells by the end of three days whereas urea production was not significantly affected. Metabolic network flexibility analysis (MNFA) demonstrated that by the end of the three day period, 0.3 mM triadimefon treated cells exhibited a major switch in hepatic metabolism by producing glucose, instead of glucose consumption. We also observed fatty acid oxidation instead of fatty acid synthesis in 0.3 mM triadimefon treated cells. Fatty acid oxidation also caused higher flux through the TCA cycle which in turn drove gluconeogenesis in these cells. It is likely that fatty acid oxidation is active in order to supply energy that is required by the phase I oxidation of triadimefon detoxification.","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121083687","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}
{"title":"A Comparative Study of a Novel AE-nLMS Filter and Two Traditional Filters in Predicting Respiration Induced Motion of the Tumor","authors":"Ke Huang, Ivan Buzurovic, Yan Yu, T. Podder","doi":"10.1109/BIBE.2010.53","DOIUrl":"https://doi.org/10.1109/BIBE.2010.53","url":null,"abstract":"Prediction of tumor motion is one of the important steps in active tracking of tumor and dynamic delivery of radiation dose to tumor. In this paper, we have presented a novel adaptive acceleration-enhanced normalized least mean squares (AE-nLMS) prediction filter based on the adaptive normalized least mean squares (nLMS) filter with predicted acceleration and ratio between the real and predicted acceleration taken into account. We have compared the performances of nLMS, artificial neural network (ANN), and AE-nLMS filter for predicting the respiration motion during normal and irregular respiration. The results revealed that the ANN filter has the best performance in the prediction of normal respiration motion, whereas the AE-nLMS filter outperformed other filters in the prediction of irregular respiration motion.","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115310164","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}
{"title":"Space Efficient Diagonal Linear Space Sequence Alignment","authors":"Gandhi Arpit, Raghavendra Adiga, Kuruvilla Varghese","doi":"10.1109/BIBE.2010.47","DOIUrl":"https://doi.org/10.1109/BIBE.2010.47","url":null,"abstract":"Smith-Waterman and Needleman-Wunsch are the most popular algorithms used for pairwise sequence alignment. The space and time complexity of these algorithms are quadratic. The biological sequences are composed of millions of base pairs. Hence, the quadratic space complexity becomes costlier in terms of storage requirement and performance. FastLSA algorithm addresses this problem by adapting to the amount of available memory. Minimum memory requirement for FastLSA is a linear function of sequence length, however if more memory is available, then it achieves better performance using the extra available memory. In this paper, we present Diagonal Linear Space Alignment algorithm which is an improvement over FastLSA. Our algorithm is adaptable to the amount of memory available, like FastLSA, but it stores the diagonals of the Dynamic Programming matrix unlike FastLSA which stores the rows and columns. We have analytically and experimentally proved that our algorithm performs better than FastLSA. Experimental results show that the proposed Diagonal Linear Space Alignment algorithm reduces the memory requirement by about 36% to 40% compared to FastLSA for similar performance in time. For longer sequences, our algorithm offers more performance gain over FastLSA.","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"598 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133557097","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}
{"title":"A Noninvasive Multimodal Sono-contrast NIR Spectroscopy System for Breast Cancer Diagnosis","authors":"K. Yan, T. Podder, Ke Huang, Yan Yu, L. Liao","doi":"10.1109/BIBE.2010.55","DOIUrl":"https://doi.org/10.1109/BIBE.2010.55","url":null,"abstract":"We have developed a multimodal imaging system that combines three modalities, optical spectroscopy, ultrasonography and acoustic radiation force (ARF) for improving diagnosis of breast cancer based on noninvasive interrogation of vasculature. This paper presents a detailed system design. The safety issues regarding the use of laser and ultrasound have also been addressed in this paper. The maximum exposure to skin for laser was controlled within 0.2 W•cm-2 (ANSI Z136.1); exposure from ARF fields were maintained below the FDA diagnostic limit (0.72 W•cm-2). This multimodal system has the potential to improve tumor detection by deploying ARF to produce a measurable difference in the dynamic behavior of the tissue blood supply environment as interrogated by optical spectroscopy, which was demonstrated to be highly diagnostic in a murine tumor model. Pilot clinical study is being carried out.","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130327784","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}
{"title":"Prediction of Gene Ontology Annotations Based on Gene Functional Clustering","authors":"M. Tagliasacchi, Roberto Sarati, M. Masseroli","doi":"10.1109/BIBE.2010.69","DOIUrl":"https://doi.org/10.1109/BIBE.2010.69","url":null,"abstract":"We propose an algorithm that predicts potentially missing Gene Ontology annotations, in order to speed up the time-consuming annotation curation process. The proposed method extends a previous work based on the singular value decomposition of the gene-term annotation matrix and incorporates gene clustering, based on gene functional similarity computed by means of the Gene Ontology annotations. We tested the prediction method by performing K-fold cross-validation on the genomes of two organisms, Saccharomyces cerevisiae (SGD) and Drosophila melanogaster (FlyBase).","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115505658","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}
Hamid Ravaee, A. Masoudi-Nejad, Saeed Omidi, A. Moeini
{"title":"Improved Immune Genetic Algorithm for Clustering Protein-Protein Interaction Network","authors":"Hamid Ravaee, A. Masoudi-Nejad, Saeed Omidi, A. Moeini","doi":"10.1109/BIBE.2010.36","DOIUrl":"https://doi.org/10.1109/BIBE.2010.36","url":null,"abstract":"Clustering protein-protein interaction network aims to find functional modules and protein complexes. There are many computational graph clustering methods that are used in this field, but few of them are intelligent computational methods. In this paper, we present a novel improved immune genetic algorithm to find dense subgraphs based on efficient vaccination method, variable-length antibody schema definition and new local and global mutations.","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128294787","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}
{"title":"Finding Dynamic Modules of Biological Regulatory Networks","authors":"F. Ay, Thang N. Dinh, M. Thai, Tamer Kahveci","doi":"10.1109/BIBE.2010.31","DOIUrl":"https://doi.org/10.1109/BIBE.2010.31","url":null,"abstract":"Often groups of genes in regulatory networks, also called modules, work collaboratively on similar functions. Mathematically, the modules in a regulatory network has often been thought as a group of genes that interact with each other significantly more than the rest of the network. Finding such modules is one of the fundamental problems in understanding gene regulation. In this paper, we develop a new approach to identify modules of genes with similar functions in biological regulatory networks (BRNs). Unlike existing methods, our method recognizes that there are different types of interactions (activation, inhibition), these interactions have directions and they take place only if the activity levels of the activating (or inhibiting) genes are above certain thresholds. Furthermore, it also considers that as a result of these interactions, the activity levels of the genes change over time even in the absence of external perturbations. Here we addresses both the dynamic behavior of gene activity levels and the different interaction types by an incremental algorithm that is scalable to the organism wide BRNs with many dynamic steps. Our experimental results suggest that our method can identify biologically meaningful modules that are missed by traditional approaches.","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128931064","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}
{"title":"Detection of Errors and Inconsistencies in Biomolecular Databases through Integrative Approaches and Quality Controls","authors":"M. Masseroli, Giorgio Ghisalberti, L. Tettamanti","doi":"10.1109/BIBE.2010.60","DOIUrl":"https://doi.org/10.1109/BIBE.2010.60","url":null,"abstract":"Most of the available biomolecular data are scattered in many databases, are computationally derived and include errors and inconsistencies. Here we show an integrative approach and a set of automatic procedures to test the quality of genomic and proteomic data from several different biomolecular databases integrated in our GFINDer data warehouse (http://www.bioinformatics.polimi.it/GFINDer/).","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121381725","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}
{"title":"Prediction of Catalytic Residues in Proteins Using a Consensus of Prediction (CoP) Approach","authors":"N. Petrova, Cathy H. Wu","doi":"10.1109/BIBE.2010.44","DOIUrl":"https://doi.org/10.1109/BIBE.2010.44","url":null,"abstract":"One of the aims of the Protein Structure Initiative (PSI) in the post genome-sequencing era is to elucidate biochemical and biophysical functions of each protein structure. Thus, the development of new methods for a large-scale analysis/annotation of protein functional residues is inevitable. Currently existing methods are not capable to do so due to the lack of automation, availability, and/or poor performance. In our previous work we were able to improve the accuracy of the prediction to ~86%, although the number of false-positives remained high. In this paper we present a fully-automated method for the prediction of catalytic residues in proteins that improves accuracy by reduction of false-positives, and is applicable for a large-scale analysis. Here, catalytic residues are predicted by machine learning approach followed by hierarchical analysis of the predicted residues. The capability of the method was tested on diverse family of hydrolytic enzymes with a/b hydrolase fold with widely differing phylogenetic origins and catalytic functions. The method was executed manually and then fully reproduces automatically. In the manual analysis, in 17 enzymes, the method correctly predicted all 3 residues of the catalytic triad with 3 false-positives out of 282 residues on average. Our method successfully eliminates the number of false-positives, while being applicable for a large-scale analysis of the protein function.","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128371811","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}
{"title":"Towards Temperature Dependent Coarse-grained Potential of Side-chain Interactions for Protein Folding Simulations","authors":"S. Ołdziej, C. Czaplewski, A. Liwo, H. Scheraga","doi":"10.1109/BIBE.2010.50","DOIUrl":"https://doi.org/10.1109/BIBE.2010.50","url":null,"abstract":"Based on the results of our recent work on the determination of the potentials of mean force of pairs of models of amino-acid side chains in water, in this work we make an attempt at introducing temperature-dependent side chain – side chain interaction potentials in our coarse-grained UNRES energy function. For hydrophobic pairs as well as oppositely-charged pairs, two functional forms are introduced, one of which implies a linear dependence of the free energy of interactions on temperature and the other one a hyperbolic-tangent dependence. The free energy of the interactions of other pairs is assumed to be independent of temperature. With the example of the N-terminal part of the B-domain of staphylococcal protein A, we demonstrate that, with this temperature dependence, the radius of gyration and the root-mean-square deviation from the native structure grow less steeply with temperature and the heat-capacity peak is lower than that obtained with temperature-independent side chain – side chain potentials. This demonstrates that ignoring the increase of the strength of hydrophobic interactions with increasing temperature in coarse-grained force fields is likely to result in grossly wrong predictions of the thermodynamics of folding and of the process of thermal unfolding made with such force fields.","PeriodicalId":330904,"journal":{"name":"2010 IEEE International Conference on BioInformatics and BioEngineering","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128557073","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}