Researchers in BiHELab focus their work on recent advances in geriatrics and neurodegeneration, ranging from basic science to clinical and pharmaceutical developments. BiHELab’s goal is to help bridge the translational gap from data to models and from models to drug discovery and personalized therapy by fostering collaborations and developing original quantitative approaches to biological and clinical problems..
Researchers in CARGO Lab have been effectively using the Blue Gene/Q Platform (BGQ) at SOSCIP (Southern Ontario Smart Computing Innovation Platform), which is designed to handle large-scale applications that require massive parallel processing power. The SOSCIP platform, Canada’s fastest supercomputer, is a research and development consortium that pairs academic and industry researchers with advanced computing tools to fuel innovation leadership in Canada within the areas of agile computing, health, water, energy, cities, mining, advanced manufacturing, digital media and cybersecurity. The consortium supports collaborative research projects between academic researchers and industry partners (SMEs and large companies) that aim to solve complex problems, develop products and services. On the BGQ, certain algorithms have exhibited a 2000-fold speedup, which can considerably increase the applicability of various algorithmic techniques..
As a university of science and technology, ETH Zurich is committed to the study of a diverse range of subjects, which allows knowledge to be shared and combined in original and future-oriented ways. The sixteen departments cover a broad academic spectrum, while all kinds of strategic initiatives, competence centres and networks encourage cross-disciplinary cooperation.
The establishment of a new Research Center entitled ‘Research Center on Computational Biomarkers (RCCBM)’ was announced on November 2016 on Wilfrid Laurier University’s Waterloo campus by the Directors of the CARGO Lab and BiHELab. The center activities, will be focused on studying human biomarkers. Professors Ilias Kotsireas and Panagiotis Vlamos stated that the future aims of precision medicine will be based on personalized measurements of specific biomarkers. The Bioinformatics and Human Electrophysiology Lab of the Department of Informatics of the Ionian University is tracing new biomarkers concerning neurodegenerative diseases and constructs frailty functions depending on them. The CARGO Lab of Wilfrid Laurier University develops and implements sophisticated data mining algorithmic techniques which can be applied to the analysis of clinical data, providing exact results for the evolution of the biomarkers, involved in specific biological mechanisms.
The Center’s activities are focused on studying human biomarkers, especially those enabled in neurodegeneration, while the future aims of precision medicine will be based on personalized measurements of specific human biomarkers. The two laboratories combine their work in the direction of establishing new diagnostic algorithms providing a precise diagnostic or even prognostic profile for individuals.
RCCBM will engage in collaboration opportunities with health organizations, hospitals and pharmaceutical companies in Canada, in order to gather and evaluate clinical date at a large scale. The center will encompass tools from Applied Mathematics, Data Mining, Modeling, Biophysics, Biochemistry, Bioinformatics, Neuroinformatics, High‐performance computing and Computational Mathematics in Biology.
The center is hosted at Wilfrid Laurier University’s Waterloo campus.
Dr. Panayiotis Vlamos is an Associate Professor and Head of the Department of Informatics at the Ionian University. He received his Diploma in Mathematics from the University of Athens and his Ph.D. degree in Mathematics from the National Technical University of Athens, Greece. He is the director of “Bioinformatics and Human Electrophysiology Lab” and of “Computational Modeling Lab” at the Department of Informatics, Ionian University.
My research is in the areas of symbolic computation and combinatorial designs. I use algorithmic, meta-heuristic and high-performance computing techniques to study existence questions for combinatorial designs. I am interested in theoretical and algorithmic aspects of solving systems of polynomial equations.
Senior Research associate at ETH Health-IS Lab Health, Professor at ETH Zurich & University of St. Gallen, University of California, San Francisco and Trinity College, Dublin will contribute with their work in RCCBM. Dr. Ioannis Tarnanas has been also selected for the 2016 Global Brain Health Institute (GBHI) Scholars program. GBHI trains international health providers as leaders, advocates, and key stakeholders in the global fight against dementia. Also, He is an Atlantic Fellow for Equity in Brain Health with GBHI Based at Trinity College Dublin & Swiss Neuro Foundation.
In the field of neuroscience, Prof. Paxinos is the author of the most cited publication internationally (The Rat Brain in Stereotaxic Coordinates; Paxinos and Watson, 1986.).This is the third most cited book in science after Molecular Cloning and the Diagnostic and Statistical Manual of Mental Disorders. Paxinos has published 46 research books, 145 refereed journal articles, 30 book chapters, and 17 CDROMs. He has identified 90 nuclei (areas) in the rat and human brains. Comparing rats and humans, he has identified 61 homologous nuclei. He has identified 180 nuclei and homologies in birds. He was the first to produce a reliable stereotaxic space for the brain of rats, mice, and primates — a factor fueling the explosion in neuroscience research since the 1980s. He developed the first comprehensive nomenclature and ontology for the brain, covering humans, birds, and developing mammals. Prof. Paxinos’ novel presentation was the first satellte event for GeNeDis 2018.
Professor of Medicine and leader of the Kentros research group at the Kavli Institute of Systems Neuroscience, NTNU. Kentros’ laboratory takes advantage of his dual molecular and neurophysiological background by combining the anatomical specificity of molecular genetics with in vivo electrophysiological recordings and anatomical analysis. The lab uses mice capable of driving the expression of transgenes in particular subsets of neurons in brain areas involved in learning and memory to determine their precise connectivity and to modulate their neural activity while recording from other cell types. In this way, the lab investigates the anatomical and functional circuitry underlying learning and memory.
Michael Harney is a Bioinformatician with the Enterprise Genomics Core at Intermountain Healthcare focusing on research in Next Generation Sequencing, machine-learning and using HPC to assist personalized medicine through genomics. He has developed and patented algorithms in signal processing and machine learning for scientific and industrial applications. He also has experience in developing applications that analyze clinical data, extracting metadata and determining data lineage. He has an MS in Bioinformatics from Johns Hopkins University and is on the editorial board for the American Journal of Oncological Research.
Dr. Jeffery Jones is the principal investigator and Professor of Psychology at Wilfrid Laurier University. He is also Director of the Laurier Centre for Cognitive Neuroscience, and a researcher at the Sun Life Movement Disorders Research and Rehabilitation Centre, and The Manfred and Penny Conrad Institute for Music Therapy Research. His research interests include: sensory-motor control during speech, singing, and music production, as well as multisensory perception. Applied work looks at communication disorders caused by Parkinson's disease, stuttering, as well as attention and cognitive loads during communication while driving. Techniques used include behavioural measures, EEG, and fMRI.
Phivos Mylonas is a Senior Researcher at the Institute of Communication and Computer Systems of National Technical University of Athens. His research interest lie in the areas of Multimedia Technologies, Content-based Information Retrieval, Knowledge Acquisition in Multimedia, Human-Computer Interaction, Computer Graphics, Context in Multimedia, Visual Context, Context and the Semantic Web, Personalization, User Profiling, User Preferences Extraction, Ontologies & Personalization, RDF, Reification, Semantic Web personalization, Multimedia Analysis, Machine Learning Databases, Data Mining: Association rules, Clustering & Classification problems, E-learning, Online courses, Collaborative learning, Descriptions of Multimedia Content: MPEG-7 Metadata, MPEG-7 Relations, Fuzzy information retrieval: Fuzzy Entities, Fuzzy Relations
Since the decoding of the Human Genome in 2003, bioinformatics, data mining, and machine learning techniques have been involved in uncovering patterns and increasing amounts and types of different data produced by profiling technologies applied to clinical samples, animal models, and cellular systems. Yet, progress on unravelling biological mechanisms, that have been implicated in the pathogenesis of many diseases, has been restricted, in part due to the characteristic complexity of biological systems. Although scientific community has achieved notable progress in deciphering the areas of cancer, cardiovascular and metabolic diseases, neurodegenerative diseases have proved to be more perplexed and very challenging.
Afflicted neurons in most neurodegenerative diseases display in general complicated and dissimilar pathological features before the catastrophic incidence of vast neuronal loss at the late stages of the diseases. The complex nature of neuronal pathophysiology inevitably implicates system wide alterations in fundamental cellular mechanisms such as transcriptional regulators and signal cascades as a cause. Moreover, most clinical trials into treatments for neurodegenerative diseases and especially for Alzheimer’s disease have failed.
A probable reason for the high failure rate is that treatments are being tested on those who already have irreversible impairment to the brain. So, treatments that slow or stop further neuron deterioration will be more effective if they are applied at earlier stages of the disease. Nowadays there is a clear need for a widely available, inexpensive and reliable method to early screen for these diseases. Also, by detecting dementia at earlier stages, it should be possible to design better clinical trials for treatments that make a real difference and improve people’s lives.
Neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease are a global health, economic and social emergency. More than 40 million people worldwide are estimated to suffer from Alzheimer’s disease and related disorders and predictions suggest this number may double by 2050.
Modeling and simulating the molecular processes of biological cells and tissues is a craft and an art. In “Computational Models for Neurodegeneration” workshop a panel of bioinformatics and modeling approaches that have recently been developed to identify candidate mechanisms of neurodegenerative diseases based on publicly available data and knowledge will be described by prominent scientists. In the Computational Models for Neurodegeneration workshop, participants will be enlightened in specific topics that include: Applied Mathematics, Data Mining, Modeling, Biophysics, Biochemistry, Bioinformatics, Neuroinformatics and Computational Mathematics in Biology. The purpose of this workshop is to bring together experts from the mathematical, computational, and medical scientist’s communities and provide a platform for the exchange of ideas. The workshop is envisioned to survey the state-of-the-art in modeling, mathematical analysis, and computational practice mostly on the field of neurodegenerative diseases, while exploring new application domains and promoting new collaborations..
Siv Sivaloganathan, University of Waterloo
Panayiotis Vlamos, Ionian University
Ioannis Tarnanas, ETH University Zurich
Michael Harney, Intermountain Healthcare IMC, Enterprise Genomics Core
Ilias Kotsireas, WLU
Stanley Liang, York University