Heuristic non parametric collateral missing value imputation : A step towards robust post-genomic knowledge discovery
- Sehgal, Muhammad Shoaib B, Gondal, Iqbal, Dooley, Laurence, Coppel, Ross
- Authors: Sehgal, Muhammad Shoaib B , Gondal, Iqbal , Dooley, Laurence , Coppel, Ross
- Date: 2008
- Type: Text , Conference paper
- Relation: Third IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB 2008) Vol. 5625
- Full Text:
- Reviewed:
- Description: Microarrays are able to measure the patterns of expression of thousands of genes in a genometo give profiles that faciliate much faster analysis of biological process for diagnosis, prognosis and tailored drug discovery. Microarrays, however commonly have missing values, various algorithms have been proposed including Collateral Missing Value Estimation (CMVE), Bayesian Principal Component Analysis (BPCA), Least Square Impute (LSImpute). Local Least Square Impute (LLSImpute) and K-Nearest Neighbour (KNN).
- Authors: Sehgal, Muhammad Shoaib B , Gondal, Iqbal , Dooley, Laurence , Coppel, Ross
- Date: 2008
- Type: Text , Conference paper
- Relation: Third IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB 2008) Vol. 5625
- Full Text:
- Reviewed:
- Description: Microarrays are able to measure the patterns of expression of thousands of genes in a genometo give profiles that faciliate much faster analysis of biological process for diagnosis, prognosis and tailored drug discovery. Microarrays, however commonly have missing values, various algorithms have been proposed including Collateral Missing Value Estimation (CMVE), Bayesian Principal Component Analysis (BPCA), Least Square Impute (LSImpute). Local Least Square Impute (LLSImpute) and K-Nearest Neighbour (KNN).
How to improve postgenomic knowledge discovery using imputation
- Sehgal, Muhammad Shoaib B, Gondal, Iqbal, Dooley, Laurence, Coppel, Ross
- Authors: Sehgal, Muhammad Shoaib B , Gondal, Iqbal , Dooley, Laurence , Coppel, Ross
- Date: 2009
- Type: Text , Journal article
- Relation: Eurasip Journal on Bioinformatics and Systems Biology Vol. 2009, no. 1 (2009), p. 1-14
- Full Text:
- Reviewed:
- Description: While microarrays make it feasible to rapidly investigate many complex biological problems, their multistep fabrication has the proclivity for error at every stage. The standard tactic has been to either ignore or regard erroneous gene readings as missing values, though this assumption can exert a major influence upon postgenomic knowledge discovery methods like gene selection and gene regulatory network (GRN) reconstruction. This has been the catalyst for a raft of new flexible imputation algorithms including local least square impute and the recent heuristic collateral missing value imputation, which exploit the biological transactional behaviour of functionally correlated genes to afford accurate missing value estimation. This paper examines the influence of missing value imputation techniques upon postgenomic knowledge inference methods with results for various algorithms consistently corroborating that instead of ignoring missing values, recycling microarray data by flexible and robust imputation can provide substantial performance benefits for subsequent downstream procedures
- Authors: Sehgal, Muhammad Shoaib B , Gondal, Iqbal , Dooley, Laurence , Coppel, Ross
- Date: 2009
- Type: Text , Journal article
- Relation: Eurasip Journal on Bioinformatics and Systems Biology Vol. 2009, no. 1 (2009), p. 1-14
- Full Text:
- Reviewed:
- Description: While microarrays make it feasible to rapidly investigate many complex biological problems, their multistep fabrication has the proclivity for error at every stage. The standard tactic has been to either ignore or regard erroneous gene readings as missing values, though this assumption can exert a major influence upon postgenomic knowledge discovery methods like gene selection and gene regulatory network (GRN) reconstruction. This has been the catalyst for a raft of new flexible imputation algorithms including local least square impute and the recent heuristic collateral missing value imputation, which exploit the biological transactional behaviour of functionally correlated genes to afford accurate missing value estimation. This paper examines the influence of missing value imputation techniques upon postgenomic knowledge inference methods with results for various algorithms consistently corroborating that instead of ignoring missing values, recycling microarray data by flexible and robust imputation can provide substantial performance benefits for subsequent downstream procedures
Gene regulatory network modeling via global optimization of high-order dynamic Bayesian network
- Nguyen, Vinh, Chetty, Madhu, Coppel, Ross, Wangikar, Pramod
- Authors: Nguyen, Vinh , Chetty, Madhu , Coppel, Ross , Wangikar, Pramod
- Date: 2012
- Type: Text , Journal article
- Relation: BMC Bioinformatics Vol. 13, no. 131 (2012), p. 1-16
- Full Text:
- Reviewed:
- Description: Abstract Background Dynamic Bayesian network (DBN) is among the mainstream approaches for modeling various biological networks, including the gene regulatory network (GRN). Most current methods for learning DBN employ either local search such as hill-climbing, or a meta stochastic global optimization framework such as genetic algorithm or simulated annealing, which are only able to locate sub-optimal solutions. Further, current DBN applications have essentially been limited to small sized networks. Results To overcome the above difficulties, we introduce here a deterministic global optimization based DBN approach for reverse engineering genetic networks from time course gene expression data. For such DBN models that consist only of inter time slice arcs, we show that there exists a polynomial time algorithm for learning the globally optimal network structure. The proposed approach, named GlobalMIT+, employs the recently proposed information theoretic scoring metric named mutual information test (MIT). GlobalMIT+ is able to learn high-order time delayed genetic interactions, which are common to most biological systems. Evaluation of the approach using both synthetic and real data sets, including a 733 cyanobacterial gene expression data set, shows significantly improved performance over other techniques. Conclusions Our studies demonstrate that deterministic global optimization approaches can infer large scale genetic networks.
- Authors: Nguyen, Vinh , Chetty, Madhu , Coppel, Ross , Wangikar, Pramod
- Date: 2012
- Type: Text , Journal article
- Relation: BMC Bioinformatics Vol. 13, no. 131 (2012), p. 1-16
- Full Text:
- Reviewed:
- Description: Abstract Background Dynamic Bayesian network (DBN) is among the mainstream approaches for modeling various biological networks, including the gene regulatory network (GRN). Most current methods for learning DBN employ either local search such as hill-climbing, or a meta stochastic global optimization framework such as genetic algorithm or simulated annealing, which are only able to locate sub-optimal solutions. Further, current DBN applications have essentially been limited to small sized networks. Results To overcome the above difficulties, we introduce here a deterministic global optimization based DBN approach for reverse engineering genetic networks from time course gene expression data. For such DBN models that consist only of inter time slice arcs, we show that there exists a polynomial time algorithm for learning the globally optimal network structure. The proposed approach, named GlobalMIT+, employs the recently proposed information theoretic scoring metric named mutual information test (MIT). GlobalMIT+ is able to learn high-order time delayed genetic interactions, which are common to most biological systems. Evaluation of the approach using both synthetic and real data sets, including a 733 cyanobacterial gene expression data set, shows significantly improved performance over other techniques. Conclusions Our studies demonstrate that deterministic global optimization approaches can infer large scale genetic networks.
A model of the circadian clock in the cyanobacterium Cyanothece sp. ATCC 51142
- Nguyen, Vinh, Chetty, Madhu, Coppel, Ross, Gaudana, Sandeep, Wangikar, Pramod
- Authors: Nguyen, Vinh , Chetty, Madhu , Coppel, Ross , Gaudana, Sandeep , Wangikar, Pramod
- Date: 2013
- Type: Text , Journal article
- Relation: BMC Bioinformatics Vol. 14, no. (Supplement 2) (2013), p. s14-1-s14-9
- Full Text:
- Reviewed:
- Description: Background The over consumption of fossil fuels has led to growing concerns over climate change and global warming. Increasing research activities have been carried out towards alternative viable biofuel sources. Of several different biofuel platforms, cyanobacteria possess great potential, for their ability to accumulate biomass tens of times faster than traditional oilseed crops. The cyanobacterium Cyanothece sp. ATCC 51142 has recently attracted lots of research interest as a model organism for such research. Cyanothece can perform efficiently both photosynthesis and nitrogen fixation within the same cell, and has been recently shown to produce biohydrogen--a byproduct of nitrogen fixation--at very high rates of several folds higher than previously described hydrogen-producing photosynthetic microbes. Since the key enzyme for nitrogen fixation is very sensitive to oxygen produced by photosynthesis, Cyanothece employs a sophisticated temporal separation scheme, where nitrogen fixation occurs at night and photosynthesis at day. At the core of this temporal separation scheme is a robust clocking mechanism, which so far has not been thoroughly studied. Understanding how this circadian clock interacts with and harmonizes global transcription of key cellular processes is one of the keys to realize the inherent potential of this organism. Results In this paper, we employ several state of the art bioinformatics techniques for studying the core circadian clock in Cyanothece sp. ATCC 51142, and its interactions with other key cellular processes. We employ comparative genomics techniques to map the circadian clock genes and genetic interactions from another cyanobacterial species, namely Synechococcus elongatus PCC 7942, of which the circadian clock has been much more thoroughly investigated. Using time series gene expression data for Cyanothece, we employ gene regulatory network reconstruction techniques to learn this network de novo, and compare the reconstructed network against the interactions currently reported in the literature. Next, we build a computational model of the interactions between the core clock and other cellular processes, and show how this model can predict the behaviour of the system under changing environmental conditions. The constructed models significantly advance our understanding of the Cyanothece circadian clock functional mechanisms.
- Authors: Nguyen, Vinh , Chetty, Madhu , Coppel, Ross , Gaudana, Sandeep , Wangikar, Pramod
- Date: 2013
- Type: Text , Journal article
- Relation: BMC Bioinformatics Vol. 14, no. (Supplement 2) (2013), p. s14-1-s14-9
- Full Text:
- Reviewed:
- Description: Background The over consumption of fossil fuels has led to growing concerns over climate change and global warming. Increasing research activities have been carried out towards alternative viable biofuel sources. Of several different biofuel platforms, cyanobacteria possess great potential, for their ability to accumulate biomass tens of times faster than traditional oilseed crops. The cyanobacterium Cyanothece sp. ATCC 51142 has recently attracted lots of research interest as a model organism for such research. Cyanothece can perform efficiently both photosynthesis and nitrogen fixation within the same cell, and has been recently shown to produce biohydrogen--a byproduct of nitrogen fixation--at very high rates of several folds higher than previously described hydrogen-producing photosynthetic microbes. Since the key enzyme for nitrogen fixation is very sensitive to oxygen produced by photosynthesis, Cyanothece employs a sophisticated temporal separation scheme, where nitrogen fixation occurs at night and photosynthesis at day. At the core of this temporal separation scheme is a robust clocking mechanism, which so far has not been thoroughly studied. Understanding how this circadian clock interacts with and harmonizes global transcription of key cellular processes is one of the keys to realize the inherent potential of this organism. Results In this paper, we employ several state of the art bioinformatics techniques for studying the core circadian clock in Cyanothece sp. ATCC 51142, and its interactions with other key cellular processes. We employ comparative genomics techniques to map the circadian clock genes and genetic interactions from another cyanobacterial species, namely Synechococcus elongatus PCC 7942, of which the circadian clock has been much more thoroughly investigated. Using time series gene expression data for Cyanothece, we employ gene regulatory network reconstruction techniques to learn this network de novo, and compare the reconstructed network against the interactions currently reported in the literature. Next, we build a computational model of the interactions between the core clock and other cellular processes, and show how this model can predict the behaviour of the system under changing environmental conditions. The constructed models significantly advance our understanding of the Cyanothece circadian clock functional mechanisms.
Effective pulmonary delivery of an aerosolized plasmid DNA vaccine via surface acoustic wave nebulization
- Rajapaksa, Anushi, Ho, Jenny, Qi, Aaisha, Bischof, Robert, Nguyen, Tri-Hung, Tate, Michelle, Piedrafita, David, McIntosh, Michelle, Yeo, Leslie, Meeusen, Els, Coppel, Ross, Friend, James
- Authors: Rajapaksa, Anushi , Ho, Jenny , Qi, Aaisha , Bischof, Robert , Nguyen, Tri-Hung , Tate, Michelle , Piedrafita, David , McIntosh, Michelle , Yeo, Leslie , Meeusen, Els , Coppel, Ross , Friend, James
- Date: 2014
- Type: Text , Journal article
- Relation: Respiratory Research Vol. 15, no. 1 (2014), p. 1-12
- Full Text:
- Reviewed:
- Description: Background: Pulmonary-delivered gene therapy promises to mitigate vaccine safety issues and reduce the need for needles and skilled personnel to use them. While plasmid DNA (pDNA) offers a rapid route to vaccine production without side effects or reliance on cold chain storage, its delivery to the lung has proved challenging. Conventional methods, including jet and ultrasonic nebulizers, fail to deliver large biomolecules like pDNA intact due to the shear and cavitational stresses present during nebulization.Methods: In vitro structural analysis followed by in vivo protein expression studies served in assessing the integrity of the pDNA subjected to surface acoustic wave (SAW) nebulisation. In vivo immunization trials were then carried out in rats using SAW nebulized pDNA (influenza A, human hemagglutinin H1N1) condensate delivered via intratracheal instillation. Finally, in vivo pulmonary vaccinations using pDNA for influenza was nebulized and delivered via a respirator to sheep.Results: The SAW nebulizer was effective at generating pDNA aerosols with sizes optimal for deep lung delivery. Successful gene expression was observed in mouse lung epithelial cells, when SAW-nebulized pDNA was delivered to male Swiss mice via intratracheal instillation. Effective systemic and mucosal antibody responses were found in rats via post-nebulized, condensed fluid instillation. Significantly, we demonstrated the suitability of the SAW nebulizer to administer unprotected pDNA encoding an influenza A virus surface glycoprotein to respirated sheep via aerosolized inhalation.Conclusion: Given the difficulty of inducing functional antibody responses for DNA vaccination in large animals, we report here the first instance of successful aerosolized inhalation delivery of a pDNA vaccine in a large animal model relevant to human lung development, structure, physiology, and disease, using a novel, low-power (<1 W) surface acoustic wave (SAW) hand-held nebulizer to produce droplets of pDNA with a size range suitable for delivery to the lower respiratory airways. © 2014 Rajapaksa et al.; licensee BioMed Central Ltd.
- Authors: Rajapaksa, Anushi , Ho, Jenny , Qi, Aaisha , Bischof, Robert , Nguyen, Tri-Hung , Tate, Michelle , Piedrafita, David , McIntosh, Michelle , Yeo, Leslie , Meeusen, Els , Coppel, Ross , Friend, James
- Date: 2014
- Type: Text , Journal article
- Relation: Respiratory Research Vol. 15, no. 1 (2014), p. 1-12
- Full Text:
- Reviewed:
- Description: Background: Pulmonary-delivered gene therapy promises to mitigate vaccine safety issues and reduce the need for needles and skilled personnel to use them. While plasmid DNA (pDNA) offers a rapid route to vaccine production without side effects or reliance on cold chain storage, its delivery to the lung has proved challenging. Conventional methods, including jet and ultrasonic nebulizers, fail to deliver large biomolecules like pDNA intact due to the shear and cavitational stresses present during nebulization.Methods: In vitro structural analysis followed by in vivo protein expression studies served in assessing the integrity of the pDNA subjected to surface acoustic wave (SAW) nebulisation. In vivo immunization trials were then carried out in rats using SAW nebulized pDNA (influenza A, human hemagglutinin H1N1) condensate delivered via intratracheal instillation. Finally, in vivo pulmonary vaccinations using pDNA for influenza was nebulized and delivered via a respirator to sheep.Results: The SAW nebulizer was effective at generating pDNA aerosols with sizes optimal for deep lung delivery. Successful gene expression was observed in mouse lung epithelial cells, when SAW-nebulized pDNA was delivered to male Swiss mice via intratracheal instillation. Effective systemic and mucosal antibody responses were found in rats via post-nebulized, condensed fluid instillation. Significantly, we demonstrated the suitability of the SAW nebulizer to administer unprotected pDNA encoding an influenza A virus surface glycoprotein to respirated sheep via aerosolized inhalation.Conclusion: Given the difficulty of inducing functional antibody responses for DNA vaccination in large animals, we report here the first instance of successful aerosolized inhalation delivery of a pDNA vaccine in a large animal model relevant to human lung development, structure, physiology, and disease, using a novel, low-power (<1 W) surface acoustic wave (SAW) hand-held nebulizer to produce droplets of pDNA with a size range suitable for delivery to the lower respiratory airways. © 2014 Rajapaksa et al.; licensee BioMed Central Ltd.
- «
- ‹
- 1
- ›
- »