Pub Date : 2015-11-02DOI: 10.1109/BIBE.2015.7367692
W. Ham, Kyumann Im, Sanghun Park, Kangsan Lee, Chulgyu Song
In this paper, we propose an acoustic signal synthesizing algorithm called two-step reconstruction algorithm based on the geometrical information of ROI(region of interest). Even though we apply the same conventional reconstruction algorithm, we can obtain the better image quality of ROI by using the proposed two-step reconstruction algorithm. We comment on the mathematical minor mistakes in applying Residue theorem for the derivation of Green's function in famous paper to which many researchers are still referring. A mathematical k-wave simulation is used for comparing the image quality of ROI with or without two-step reconstruction algorithm. From the simulation results, we prove the effectiveness of proposed acoustic signal synthesizing of two-step reconstruction algorithm.
{"title":"A new reconstruction algorithm for photoacoustic imaging based on geometric information of ROI","authors":"W. Ham, Kyumann Im, Sanghun Park, Kangsan Lee, Chulgyu Song","doi":"10.1109/BIBE.2015.7367692","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367692","url":null,"abstract":"In this paper, we propose an acoustic signal synthesizing algorithm called two-step reconstruction algorithm based on the geometrical information of ROI(region of interest). Even though we apply the same conventional reconstruction algorithm, we can obtain the better image quality of ROI by using the proposed two-step reconstruction algorithm. We comment on the mathematical minor mistakes in applying Residue theorem for the derivation of Green's function in famous paper to which many researchers are still referring. A mathematical k-wave simulation is used for comparing the image quality of ROI with or without two-step reconstruction algorithm. From the simulation results, we prove the effectiveness of proposed acoustic signal synthesizing of two-step reconstruction algorithm.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121634944","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 : 2015-11-02DOI: 10.1109/BIBE.2015.7367641
V. Dunić, N. Busarac, V. Slavkovic, R. Slavkovic
This paper aims to highlight importance of coupled thermo-mechanical analysis of structures and devices made of shape memory alloys (SMA). Ti-Ni alloys are recognized as very biocompatible SMA, so theirs usage is very often in medical purpose. Stent implants made of SMA are the best known application of such materials, so the unit cell of some typical stent model is used to demonstrate the necessity of coupled finite element based numerical analysis of such structures. The thermo-mechanical coupling is realized in partitioned approach, whereas software components for structural analysis (PAKS) and heat transfer (PAKT) have been used as suitable solutions. The SMA constitutive model is implemented into PAKS with the capability to solve large strain problems by using multiplicative decomposition of deformation gradient.
{"title":"Thermo-mechanical numerical analysis of stent unit cell","authors":"V. Dunić, N. Busarac, V. Slavkovic, R. Slavkovic","doi":"10.1109/BIBE.2015.7367641","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367641","url":null,"abstract":"This paper aims to highlight importance of coupled thermo-mechanical analysis of structures and devices made of shape memory alloys (SMA). Ti-Ni alloys are recognized as very biocompatible SMA, so theirs usage is very often in medical purpose. Stent implants made of SMA are the best known application of such materials, so the unit cell of some typical stent model is used to demonstrate the necessity of coupled finite element based numerical analysis of such structures. The thermo-mechanical coupling is realized in partitioned approach, whereas software components for structural analysis (PAKS) and heat transfer (PAKT) have been used as suitable solutions. The SMA constitutive model is implemented into PAKS with the capability to solve large strain problems by using multiplicative decomposition of deformation gradient.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"5 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120993405","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 : 2015-11-02DOI: 10.1109/BIBE.2015.7367707
M. Yiannakou, C. Damianou
The main objective of the study was to treat Alzheimer's disease (AD) plaques using focused ultrasound (FUS) induced blood brain barrier (BBB) opening with and without delivery of antibodies in a rabbit model for AD. The animal model was achieved by feeding a high cholesterol diet to rabbits for 4 months. A single spherically focused MRI compatible transducer was used which operated at 1 MHz, had a focal length of 10 cm and diameter of 4 cm. By increasing the number of sessions, the number of plaques decreased (both for antibodies, and without antibodies). This study demonstrated that by opening the BBB, it will be possible to deliver exogenous antibodies to the brain, which eliminates Amyloid β plaques.
{"title":"Amyloid beta plaque reduction with antibodies crossing the blood brain barrier opened with focused ultrasound in a rabbit model","authors":"M. Yiannakou, C. Damianou","doi":"10.1109/BIBE.2015.7367707","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367707","url":null,"abstract":"The main objective of the study was to treat Alzheimer's disease (AD) plaques using focused ultrasound (FUS) induced blood brain barrier (BBB) opening with and without delivery of antibodies in a rabbit model for AD. The animal model was achieved by feeding a high cholesterol diet to rabbits for 4 months. A single spherically focused MRI compatible transducer was used which operated at 1 MHz, had a focal length of 10 cm and diameter of 4 cm. By increasing the number of sessions, the number of plaques decreased (both for antibodies, and without antibodies). This study demonstrated that by opening the BBB, it will be possible to deliver exogenous antibodies to the brain, which eliminates Amyloid β plaques.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129706776","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 : 2015-11-02DOI: 10.1109/BIBE.2015.7367656
S. Djorovic, N. Filipovic, V. Stojić, L. Velicki
The main purpose of this study is to examine how flow field in aortic dissection is affected by its geometry and flow condition. Two models of DeBakey type I aortic dissection, which involves the entire aorta, were analyzed. Patient-specific geometries were reconstructed, based on Computed tomography (CT) scan images, in order to obtain 3D finite element meshes. Computational fluid dynamics (CFD), which uses numeric methods and algorithms for the simulation of blood flow by solving the Navier-Stokes equations on computational meshes, enhances the understanding of disease progression. For that purpose, the major fluid dynamic parameters and indicators of disease progression, such as velocity field, pressure and shear stress, were computed and analyzed. The computed results showed higher velocities in the ascending aorta, the inlet and outlet tears and the iliac arteries, in case of both models. The pressure distribution showed high zones in the ascending aorta, while the shear stress distribution showed low zones in the aneurysm part, in case of both models. In summary, the presented study can be extended to a larger patient group in a longitudinal study with the goal to determine the potential value of CFD simulations in prediction of aneurysmal growth and rupture.
{"title":"Computational simulation of blood flow in a DeBakey type I aortic dissection","authors":"S. Djorovic, N. Filipovic, V. Stojić, L. Velicki","doi":"10.1109/BIBE.2015.7367656","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367656","url":null,"abstract":"The main purpose of this study is to examine how flow field in aortic dissection is affected by its geometry and flow condition. Two models of DeBakey type I aortic dissection, which involves the entire aorta, were analyzed. Patient-specific geometries were reconstructed, based on Computed tomography (CT) scan images, in order to obtain 3D finite element meshes. Computational fluid dynamics (CFD), which uses numeric methods and algorithms for the simulation of blood flow by solving the Navier-Stokes equations on computational meshes, enhances the understanding of disease progression. For that purpose, the major fluid dynamic parameters and indicators of disease progression, such as velocity field, pressure and shear stress, were computed and analyzed. The computed results showed higher velocities in the ascending aorta, the inlet and outlet tears and the iliac arteries, in case of both models. The pressure distribution showed high zones in the ascending aorta, while the shear stress distribution showed low zones in the aneurysm part, in case of both models. In summary, the presented study can be extended to a larger patient group in a longitudinal study with the goal to determine the potential value of CFD simulations in prediction of aneurysmal growth and rupture.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129752637","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 : 2015-11-02DOI: 10.1109/BIBE.2015.7367735
Gorkem Serbes, Betul Erdogdu Sakar, N. Aydin
Transcranial Doppler (TCD) is a widely used, non-invasive, rapid and reproducible monitoring method for observing the condition of middle cerebral artery. Micro embolic signals, which appear in various clinical scenarios such as; carotid stenosis, aortic arch plaques, atrial fibrillation, myocardial infarction, patent foramen ovale and valvular stenosis, can be detected by the analysis of TCD signals. Discrete wavelet transform based methods were frequently used in literature for micro embolic signal detection. However, in all the previously used complex/non-complex discrete wavelet transform based methods, low Q-factor wavelets were employed for feature extraction. Low Q-factor wavelets have been successfully used for processing piecewise smooth signals but for the embolic signals, a discrete wavelet transform with better frequency resolution is needed. Therefore in this study, a novel Directional Dual Tree Rational Dilation Wavelet Transform (DDT-RADWT), in which the Q-factor of the analysis and synthesis filters can be adjusted due to the properties of signal of interest, is used as the feature extractor. DDT-RADWT is applied to a dataset consisting of 130 micro embolic signals and 130 non-embolic signals (65 artifacts and 65 Doppler speckles) and the obtained coefficients are used as features. In the proposed method, in order to utilize from the different frequency characteristics of micro embolic, artifact and Doppler speckle signals, the DDT-RADWT is applied with high Q-factor filters. The extracted coefficients are given to k-NN and SVM classifiers with the aim of discriminating two classes of micro embolic signals and non-embolic signals. The results show that higher general accuracy and micro embolic signal detection accuracies are obtained with high Q-factor wavelet analysis.
{"title":"A micro emboli vs non-emboli classification system based on the directional dual tree rational dilation wavelet transform","authors":"Gorkem Serbes, Betul Erdogdu Sakar, N. Aydin","doi":"10.1109/BIBE.2015.7367735","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367735","url":null,"abstract":"Transcranial Doppler (TCD) is a widely used, non-invasive, rapid and reproducible monitoring method for observing the condition of middle cerebral artery. Micro embolic signals, which appear in various clinical scenarios such as; carotid stenosis, aortic arch plaques, atrial fibrillation, myocardial infarction, patent foramen ovale and valvular stenosis, can be detected by the analysis of TCD signals. Discrete wavelet transform based methods were frequently used in literature for micro embolic signal detection. However, in all the previously used complex/non-complex discrete wavelet transform based methods, low Q-factor wavelets were employed for feature extraction. Low Q-factor wavelets have been successfully used for processing piecewise smooth signals but for the embolic signals, a discrete wavelet transform with better frequency resolution is needed. Therefore in this study, a novel Directional Dual Tree Rational Dilation Wavelet Transform (DDT-RADWT), in which the Q-factor of the analysis and synthesis filters can be adjusted due to the properties of signal of interest, is used as the feature extractor. DDT-RADWT is applied to a dataset consisting of 130 micro embolic signals and 130 non-embolic signals (65 artifacts and 65 Doppler speckles) and the obtained coefficients are used as features. In the proposed method, in order to utilize from the different frequency characteristics of micro embolic, artifact and Doppler speckle signals, the DDT-RADWT is applied with high Q-factor filters. The extracted coefficients are given to k-NN and SVM classifiers with the aim of discriminating two classes of micro embolic signals and non-embolic signals. The results show that higher general accuracy and micro embolic signal detection accuracies are obtained with high Q-factor wavelet analysis.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130230730","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 : 2015-11-02DOI: 10.1109/BIBE.2015.7367661
T. Šušteršič, Miodrag Peulić, N. Filipovic, A. Peulić
In this paper we present a method for brain tumor segmentation and assess its performance discussing parameters - complexity of initial conditions that need to be set manually, tumor surface area recognition, and computational time. The methodology includes performing segmentation on computerized tomography (CT) medical images from 37 patients. Furthermore, one approach to user friendly two- and three-dimensional tumor visualization is proposed. The results obtained in this paper can be new paradigm in the assessment of optimal approach trajectory to brain tumor in surgical operation.
{"title":"Application of active contours method in assessment of optimal approach trajectory to brain tumor","authors":"T. Šušteršič, Miodrag Peulić, N. Filipovic, A. Peulić","doi":"10.1109/BIBE.2015.7367661","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367661","url":null,"abstract":"In this paper we present a method for brain tumor segmentation and assess its performance discussing parameters - complexity of initial conditions that need to be set manually, tumor surface area recognition, and computational time. The methodology includes performing segmentation on computerized tomography (CT) medical images from 37 patients. Furthermore, one approach to user friendly two- and three-dimensional tumor visualization is proposed. The results obtained in this paper can be new paradigm in the assessment of optimal approach trajectory to brain tumor in surgical operation.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122773085","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 : 2015-11-02DOI: 10.1109/BIBE.2015.7367724
Theodoras Koutsandreas, E. Pilalis, E. Vlachavas, D. Koczan, S. Klippel, A. Dimitrakopoulou-Strauss, I. Valavanis, A. Chatziioannou
The development of several biomedical ontologies and databases for structuring and categorizing knowledge in life sciences, and particularly the ones which refer to the functions and interactions of biomolecules, have contributed to the rapid inflation of the semantic information universe that describes cellular complexity, at different scales. Together with the ever-growing number of high-throughput molecular data, generated by DNA microarray or NGS experiments, they stress the need for powerful, intuitive data representation methods, which manage to make sense out of the myriads of interactions and pinpoint those with a causal contribution to the phenotypes studied. In this paper, we present a web application, which overall combines computational methodologies and data visualization techniques, in order to deliver comprehensible illustrations of cellular complexity, for voluminous, molecular datasets, linking the individual genes, with the relevant biological processes, in which they participate, while it manages to prioritize those processes according to their involvement in the cellular phenotype studied. The application highlights molecular information (functions, processes, cellular compartments) according several criteria (enrichment score, expression, etc) sorts out regulatory hub genes, with a pivotal role in the phenotype studied, while, most importantly, novel visualization modules provide an efficient, intuitive illustration that aids easy systems' level interpretation. The pipeline is showcased here using a colon cancer dataset.
{"title":"Making sense of the biological complexity through the platform-driven unification of the analytical and visualization tasks","authors":"Theodoras Koutsandreas, E. Pilalis, E. Vlachavas, D. Koczan, S. Klippel, A. Dimitrakopoulou-Strauss, I. Valavanis, A. Chatziioannou","doi":"10.1109/BIBE.2015.7367724","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367724","url":null,"abstract":"The development of several biomedical ontologies and databases for structuring and categorizing knowledge in life sciences, and particularly the ones which refer to the functions and interactions of biomolecules, have contributed to the rapid inflation of the semantic information universe that describes cellular complexity, at different scales. Together with the ever-growing number of high-throughput molecular data, generated by DNA microarray or NGS experiments, they stress the need for powerful, intuitive data representation methods, which manage to make sense out of the myriads of interactions and pinpoint those with a causal contribution to the phenotypes studied. In this paper, we present a web application, which overall combines computational methodologies and data visualization techniques, in order to deliver comprehensible illustrations of cellular complexity, for voluminous, molecular datasets, linking the individual genes, with the relevant biological processes, in which they participate, while it manages to prioritize those processes according to their involvement in the cellular phenotype studied. The application highlights molecular information (functions, processes, cellular compartments) according several criteria (enrichment score, expression, etc) sorts out regulatory hub genes, with a pivotal role in the phenotype studied, while, most importantly, novel visualization modules provide an efficient, intuitive illustration that aids easy systems' level interpretation. The pipeline is showcased here using a colon cancer dataset.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128581946","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 : 2015-11-02DOI: 10.1109/BIBE.2015.7367654
N. Kathiresan, Rashid J. Al-Ali, P. Jithesh, Tariq AbuZaid, Ramzi Temanni, A. Ptitsyn
Advancement in Next Generation Sequencing (NGS) technology are associated with ever-increasing volume of genomic data every year. These genomic data are efficiently processed by empirical parallelism using High Performance Computing (HPC). The processed data can be used for genome-wide association studies, genetics, personalized medicine and many other areas. There are different kind of algorithms and implementations used in different phases of genome processing. In this paper, we used BWAKIT and GATK based software for processing larger volume of genomic data that are referred as "NGS workflow at SIDRA". We used BWAKIT for genome alignment and GATK for variant discovery in the NGS workflow that required larger computation and huge memory requirement respectively. We observed, the CPU utilization is not more than 45% during variant discovery and hence, it is necessary to understand the optimal selection (in terms of number of threads or cores) of the resources during the NGS workflow automation. We analyzed the performance bottleneck and application optimization in terms of "scalability" (use maximum available CPUs and memory) and "multiple instances of NGS workflow with different genome data within a node" (process more volume of genome data concurrently with limited set of CPUs and memory). We observed that, 40%, 65%, 71% and 76% improvement in performance while processing 2, 4, 8 and 16 samples concurrently using our own scheduling heuristics. As a result, our proposed NGS workflow automation will improve the performance upto 76% compared to application scalability based workflows.
{"title":"Optimization of data-intensive next generation sequencing in high performance computing","authors":"N. Kathiresan, Rashid J. Al-Ali, P. Jithesh, Tariq AbuZaid, Ramzi Temanni, A. Ptitsyn","doi":"10.1109/BIBE.2015.7367654","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367654","url":null,"abstract":"Advancement in Next Generation Sequencing (NGS) technology are associated with ever-increasing volume of genomic data every year. These genomic data are efficiently processed by empirical parallelism using High Performance Computing (HPC). The processed data can be used for genome-wide association studies, genetics, personalized medicine and many other areas. There are different kind of algorithms and implementations used in different phases of genome processing. In this paper, we used BWAKIT and GATK based software for processing larger volume of genomic data that are referred as \"NGS workflow at SIDRA\". We used BWAKIT for genome alignment and GATK for variant discovery in the NGS workflow that required larger computation and huge memory requirement respectively. We observed, the CPU utilization is not more than 45% during variant discovery and hence, it is necessary to understand the optimal selection (in terms of number of threads or cores) of the resources during the NGS workflow automation. We analyzed the performance bottleneck and application optimization in terms of \"scalability\" (use maximum available CPUs and memory) and \"multiple instances of NGS workflow with different genome data within a node\" (process more volume of genome data concurrently with limited set of CPUs and memory). We observed that, 40%, 65%, 71% and 76% improvement in performance while processing 2, 4, 8 and 16 samples concurrently using our own scheduling heuristics. As a result, our proposed NGS workflow automation will improve the performance upto 76% compared to application scalability based workflows.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"166 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127581707","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 : 2015-11-02DOI: 10.1109/BIBE.2015.7367734
X. Cao, Z. Obradovic
Gene expression data are widely used in classification tasks for medical diagnosis. Data scaling is recommended and helpful for learning the classification models. In this study, we propose a data scaling algorithm to transform the data uniformly to an appropriate interval by learning a generalized logistic function to fit the empirical cumulative density function of the data. The proposed algorithm is robust to outliers, and experimental results show that models learned using data scaled by the proposed algorithm generally outperform the ones using min-max mapping and z-score which are currently the most commonly used data scaling algorithms.
{"title":"A robust data scaling algorithm for gene expression classification","authors":"X. Cao, Z. Obradovic","doi":"10.1109/BIBE.2015.7367734","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367734","url":null,"abstract":"Gene expression data are widely used in classification tasks for medical diagnosis. Data scaling is recommended and helpful for learning the classification models. In this study, we propose a data scaling algorithm to transform the data uniformly to an appropriate interval by learning a generalized logistic function to fit the empirical cumulative density function of the data. The proposed algorithm is robust to outliers, and experimental results show that models learned using data scaled by the proposed algorithm generally outperform the ones using min-max mapping and z-score which are currently the most commonly used data scaling algorithms.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128342917","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 : 2015-11-02DOI: 10.1109/BIBE.2015.7367644
Hongtao Guo, Lingru Wang, Rong Li, Ting Hao, Guang Zheng
With limited researches, there is still lack of pathway networks of Chuan-wu (also called Aconitum carmichaelii) against rheumatoid arthritis which might provide clues for further researches. In this study, started from the chemical compounds, proteins targeted by Chuan-wu were explored. After that, pathway networks enriched with these targeted proteins were analyzed with hypergeometric distribution on threshold ofp-value set to 0.001 for pharmacology mechanism. Meanwhile, pathway networks enriched with OMIM genes of rheumatoid arthritis were also calculated for pathology analysis in the same way. Then, these two pathway networks of pharmacology and pathology were merged into one for validation and further predictions. As a result, six pathway networks were predicted which might be responsible for the therapeutic effect against rheumatoid arthritis. They are: disease, signal transduction, metabolism of proteins, cell cycle, metabolism of proteins, and developmental biology.
{"title":"Pathway enrichment analysis of Chuan-wu for rheumatoid arthritis","authors":"Hongtao Guo, Lingru Wang, Rong Li, Ting Hao, Guang Zheng","doi":"10.1109/BIBE.2015.7367644","DOIUrl":"https://doi.org/10.1109/BIBE.2015.7367644","url":null,"abstract":"With limited researches, there is still lack of pathway networks of Chuan-wu (also called Aconitum carmichaelii) against rheumatoid arthritis which might provide clues for further researches. In this study, started from the chemical compounds, proteins targeted by Chuan-wu were explored. After that, pathway networks enriched with these targeted proteins were analyzed with hypergeometric distribution on threshold ofp-value set to 0.001 for pharmacology mechanism. Meanwhile, pathway networks enriched with OMIM genes of rheumatoid arthritis were also calculated for pathology analysis in the same way. Then, these two pathway networks of pharmacology and pathology were merged into one for validation and further predictions. As a result, six pathway networks were predicted which might be responsible for the therapeutic effect against rheumatoid arthritis. They are: disease, signal transduction, metabolism of proteins, cell cycle, metabolism of proteins, and developmental biology.","PeriodicalId":422807,"journal":{"name":"2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131154091","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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