{"title":"Combination of different texture features for mammographic breast density classification","authors":"Gregoris Liasis, C. Pattichis, S. Petroudi","doi":"10.1109/BIBE.2012.6399758","DOIUrl":"https://doi.org/10.1109/BIBE.2012.6399758","url":null,"abstract":"Mammographic breast density refers to the prevalence of fibroglandular tissue as it appears on a mammogram. Breast density is not only an important risk for developing breast cancer but can also mask abnormalities. Breast density information can be used for planning individualized screening and treatment. In this work, statistical distributions of different texture descriptors and their combination are investigated with Support Vector Machines (SVMs) for objective breast density classification: Scale Invariant Feature Transforms (SIFT), Local Binary Patterns (LBP) and texton histograms. SIFT is an approach for detecting and extracting local feature descriptors that are reasonably invariant to changes in illumination, image noise, rotation, scaling and small changes in viewpoint. The SIFT descriptor is a coarse descriptor of the edges found in the keypoints. LBPs provide a robust and computationally simple way for describing pure local binary patterns in a texture. They provide information regarding the prevalence of different edge patterns and uniformity. Textons are defined under the operational definition of clustered filter responses and provide a statistical and structural unifying approach for texture characterization. The breast density classification accuracy of the SVM classifiers modeled on the histograms of the three different sets of texture features separately and their combination is evaluated on the Medical Image Analysis Society (MIAS) mammographic database and the results are presented. The combination of the statistical distributions of all the different texture features allows for the highest classification accuracy, reaching over 93%.","PeriodicalId":330164,"journal":{"name":"2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115413349","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}
Christos C. Kannas, K. Achilleos, Z. Antoniou, C. Nicolaou, C. Pattichis, Ioanna Kalvari, I. Kirmitzoglou, V. Promponas
{"title":"A workflow system for virtual screening in cancer chemoprevention","authors":"Christos C. Kannas, K. Achilleos, Z. Antoniou, C. Nicolaou, C. Pattichis, Ioanna Kalvari, I. Kirmitzoglou, V. Promponas","doi":"10.1109/BIBE.2012.6399766","DOIUrl":"https://doi.org/10.1109/BIBE.2012.6399766","url":null,"abstract":"Computer-aided drug discovery techniques have been widely used in recent years to support the development of new pharmaceuticals. Virtual screening, the computational counterpart of experimental screening, attempts to replicate the results from in vitro and in vivo methods through the use of in silico models and tools. This paper presents the LISIs platform; a web based scientific workflow system for virtual screening that has been implemented primarily for the discovery of chemoprevention agents. We describe the overall design of the system as well as the implementation of its various components. Indicative results from early applications of the system are also presented to illustrate its potential uses and functionalities.","PeriodicalId":330164,"journal":{"name":"2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE)","volume":"182 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123515801","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":"Sequence features of Compositionally Biased regions in three dimensional protein structures","authors":"S. Tamana, I. Kirmitzoglou, V. Promponas","doi":"10.1109/BIBE.2012.6399687","DOIUrl":"https://doi.org/10.1109/BIBE.2012.6399687","url":null,"abstract":"A considerable research effort has already been put on the identification (and consequently filtering) of local segments of “unusual” composition (Compositionally Biased or Low Complexity Regions; CBRs or LCRs) in protein sequences. This interest was mainly initiated due to the fact that CBR existence is known to create artifacts (i.e. biologically irrelevant hits) in sequence database search methods. Even though no general biological significance has been demonstrated for CBRs so far, they are often associated with the lack of regular structure. However, application of commonly used methods for CBR detection illustrates that instances of CBRs can be found in proteins with experimentally determined three dimensional structures. In this work, we highlight sequential properties of CBRs detected by two of the most widely used CBR detection algorithms in carefully compiled datasets of proteins with experimentally determined structures. Our goal is to shed light on the properties of CBR sequences, with the future prospect of elucidating their relation to protein three dimensional structure.","PeriodicalId":330164,"journal":{"name":"2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128583388","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}
K. Michalopoulos, M. Zervakis, N. Bourbakis, P. Giannakopoulos, M. Deiber
{"title":"Decomposition and evaluation of activity in multiple event-related trials","authors":"K. Michalopoulos, M. Zervakis, N. Bourbakis, P. Giannakopoulos, M. Deiber","doi":"10.1109/BIBE.2012.6399653","DOIUrl":"https://doi.org/10.1109/BIBE.2012.6399653","url":null,"abstract":"It is generally accepted that evoked and induced activations represent different aspects of cerebral functions during an Event Related Potentials (ERP) experiment. Independent Component Analysis (ICA) has been successfully applied to event related electroencephalography (EEG) to decompose it into a sum of spatially fixed and temporally independent components that can be attributed to underlying cortical activity. A major problem in the application of ICA is the stability of estimated independent components. In this paper we exploited the split-half approach to assess component stability. We used different measures quantifying both phase and energy aspects of the ERP, in order to distinguish evoked from induced oscillations. We applied these measures to the stable independent components derived from a dataset of progressive Mild Cognitive Impairment (PMCI) and elderly controls. We found reduced energy in the induced theta activity in PMCI subjects, in accordance with previous studies. In addition, PMCI subjects presented lower phase-locking values and diminished late alpha band energy in contrast to controls.","PeriodicalId":330164,"journal":{"name":"2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126701464","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}
A. Walter, G. Naros, Alexander Roth, W. Rosenstiel, A. Gharabaghi, M. Bogdan
{"title":"A brain-computer interface for chronic pain patients using epidural ECoG and visual feedback","authors":"A. Walter, G. Naros, Alexander Roth, W. Rosenstiel, A. Gharabaghi, M. Bogdan","doi":"10.1109/BIBE.2012.6399654","DOIUrl":"https://doi.org/10.1109/BIBE.2012.6399654","url":null,"abstract":"Electrocorticography (ECoG) offers the possibility of decoding movement intention even in the absence of motor control, making it a powerful signal source for brain-computer interfaces (BCI). We designed a BCI that translates attempts to move the hand into movements of a video of an opening hand to investigate its use for pain therapy and stroke rehabilitation. One patient with phantom limb pain after amputation of the arm and one patient suffering from chronic pain and paralysis after a stroke trained with this BCI for several sessions. Signals were acquired with epidural ECoG grids placed over the motor cortex contralateral to the affected or missing hand. The analysis of data obtained in screening sessions with cued attempted movements showed highly significant (p <; 0.01, permutation test) r2 values for the discrimination between movement and rest conditions for most frequencies up to 200 Hz. Both patients acquired control of the BCI system which was verified by the evaluation of three measures of the ability to start and stop the video application. In particular, both patients learned to reliably start the video application in all trials. This demonstrates that it is feasible for patients with phantom limb pain and chronic pain as well as paralysis after stroke to operate a BCI that targets their missing or impaired limb, making it a potentially useful tool for new approaches in pain therapy and stroke rehabilitation.","PeriodicalId":330164,"journal":{"name":"2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121481477","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":"Continuous plantar pressure modeling using sparse sensors","authors":"S. Ostadabbas, M. Nourani, M. Pompeo","doi":"10.1109/BIBE.2012.6399641","DOIUrl":"https://doi.org/10.1109/BIBE.2012.6399641","url":null,"abstract":"The foot complications constitute a tremendous challenge for diabetic patients, caregivers, and the healthcare system. With current technology, in-shoe monitoring systems can be implemented to continuously monitor foot's at-risk ulceration sites and send feedback to patients and physicians. The few available high resolution in-shoe pressure measuring systems are extremely expensive and targeting clinical use only. The more affordable price ranges can be reached by limiting the number of sensors in the shoe. Precise subject-specific sensor placement is still a challenge in such platforms. Moreover, there is no good way to estimate pressure on other points of the foot. In this paper, we address these technical challenges by proposing SCPM algorithm that reconstructs a continuous foot plantar pressure image from a sparse set of sensor readings. Using our technique, sensor placement can be the same in every electronic insole. However, the SCPM's trained parameters are unique for every subject and foot.","PeriodicalId":330164,"journal":{"name":"2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121666920","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":"Binding site extraction by similar subgraphs mining from protein molecular surfaces","authors":"Natsumi Kurumatani, Hiroyuki Monji, T. Ohkawa","doi":"10.1142/S0218213014600070","DOIUrl":"https://doi.org/10.1142/S0218213014600070","url":null,"abstract":"Most proteins express their functions by binding with other proteins or molecular compounds called ligands. The local portion involved in binding is called a binding site. The characteristics of the binding site often determine the function of the protein, so clarifying the location of the binding site of the protein helps analyze the function of proteins. Binding sites that bind to similar ligands often have common surface structures. Such common structures are called surface motifs. Therefore, extracting the surface motifs among several proteins with similar functions improves binding site prediction. We propose a method of predicting binding sites by extracting the surface motifs that are frequently observed in only a specific group, which means a set of proteins that bind to the same ligand. Since most binding sites have concave structures called pockets, the pockets are compared and common structures are searched for to extract the surface motifs by applying similar graph mining to the pocket data, which are represented as graphs, to find the frequent subgraphs among the pockets of several proteins. In addition, the common binding sites across several groups can be predicted in such a way to integrate more than one group. Applying our proposed method to a set of 37 proteins of five groups, we achieved success rates of binding site prediction over 40% and 50% for more than half of the groups without group integration and using integration, respectively.","PeriodicalId":330164,"journal":{"name":"2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115963676","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":"The effects of near optimal growth solutions in genome-scale human cancer metabolic model","authors":"E. Tzamali, V. Sakkalis, K. Marias","doi":"10.1109/BIBE.2012.6399774","DOIUrl":"https://doi.org/10.1109/BIBE.2012.6399774","url":null,"abstract":"Cancer cells inefficiently produce energy through glycolysis even in ample oxygen, a phenomenon known as “aerobic glycolysis”. A characteristic of the rapid and incomplete catabolism of glucose is the secretion of lactate. Genome-scale metabolic models have been recently employed to describe the glycolytic phenotype of highly proliferating human cancer cells. Genome-scale models describe genotype-phenotype relations revealing the full extent of metabolic capabilities of genotypes under various environmental conditions. The importance of these approaches in understanding some aspects of cancer complexity, as well as in cancer diagnostics and individualized therapeutic schemes related to metabolism is evident. Based on previous metabolic models, we explore the metabolic capabilities and rerouting that occur in cancer metabolism when we apply a strategy that allows near optimal growth solution while maximizing lactate secretion. The simulations show that slight deviations around the optimal growth are sufficient for adequate lactate release and that glucose uptake and lactate secretion are correlated at high proliferation rates as it has been observed. Inhibition of lactate dehydrogenase-A, an enzyme involved in the conversion of pyruvate to lactate, substantially reduces lactate release. We also observe that activating specific reactions associated with the migration-related PLCγ enzyme, the proliferation rate decreases. Furthermore, we incorporate flux constraints related to differentially expressed genes in Glioblastoma Multiforme in an attempt to construct a Glioblastoma-specific metabolic model and investigate its metabolic capabilities across different glucose uptake bounds.","PeriodicalId":330164,"journal":{"name":"2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134056122","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}
R. Braojos, G. Ansaloni, David Atienza Alonso, F. Rincón
{"title":"Embedded real-time ECG delineation methods: A comparative evaluation","authors":"R. Braojos, G. Ansaloni, David Atienza Alonso, F. Rincón","doi":"10.1109/BIBE.2012.6399715","DOIUrl":"https://doi.org/10.1109/BIBE.2012.6399715","url":null,"abstract":"Wireless sensor nodes (WSNs) have recently evolved to include a fair amount of computational power, so that advanced signal processing algorithms can now be embedded even in these extremely low-power platforms. An increasingly successful field of application of WSNs is tele-healthcare, which enables continuous monitoring of subjects, even outside a medical environment. In particular, the design of solutions for automated and remote electrocardiogram (ECG) analysis has attracted considerable research interest in recent years, and different algorithms for delineation of normal and pathological heart rhythms have been proposed. In this paper, some of the most promising techniques for filtering and delineation of ECG signals are explored and comparatively evaluated, describing their implementation on the state-of-the-art IcyHeart WSN. The goal of this paper is to explore the trade-offs implied in the different settings and the impact of design choices for implementing “smart” WSNs dedicated to monitoring ECG bio-signals.","PeriodicalId":330164,"journal":{"name":"2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131526817","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}
A. Achilleos, Charalambos Loizides, T. Stylianopoulos, G. Mitsis
{"title":"Linear dynamic modelling and Bayesian forecasting of tumor evolution","authors":"A. Achilleos, Charalambos Loizides, T. Stylianopoulos, G. Mitsis","doi":"10.1109/BIBE.2012.6399747","DOIUrl":"https://doi.org/10.1109/BIBE.2012.6399747","url":null,"abstract":"We consider a linear dynamic model for tumor growth evolution. A number of temporal statistical models for tumor growth exist in the literature. In the majority of these cases the employed models are formulated in a deterministic context, providing no information on their uncertainty. Some of these are theoretically well defined and very useful in practice, e.g. to define general optimal treatment protocols through nonlinear constrained optimization. Nevertheless a challenging task is the estimation of the model parameters for a specific individual since, especially in humans, it is not feasible to collect a large number of tumor size values with respect to time, as the tumor is removed immediately after diagnosis in most cases. Therefore, we suggest a probabilistic model for personalized sequential tumor growth prediction, given only a few observed data and an a priori information regarding the average response to a specific type of cancer of the population to which the subject belongs. We validated the proposed model with experimental data from mice and the results are promising.","PeriodicalId":330164,"journal":{"name":"2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE)","volume":"409 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124345585","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}