Tutorial
On this tutorial, 90 minutes long, you shall learn biomathematics and prepare for the webinars to come. We shall mixture theory with codes, examples, and discussions. The aim is giving non-experts a glimpse on biomathematics, and people familar with biomathematics a notion on how computational intelligence can be useful on this ever-growing area.
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See more details on the CBIC page: tutorials.
A crash course in biomathematics,
by Jorge Guerra Pires, PhD
Webinars
An introduction to whole-cell model,
by Jonathan Karr, PhD, Fellow at Mount Sinai School of Medicine, New York, USA
On this webinar, you shall get to know the concept of "whole-cell model." This model is a mathematical attempt to model the human cell, for possible future applications in medicine and biology.
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This is a classical talk by Jonathan Karr, he shall highlight how machine learning can be useful on some steps of the model building process. Futhermore, we shall leave space for discussions on how computational intelligence can support in future endeavors.
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This is a nice opportunity for both side: computational intelligence and biomathematicians; the former can get to know an ever-growing demand of people working with computational intelligence related areas, and the latter can get to know more about possible applications of computational intelligence in modeling.
Horizontal gene transfer constraint the evolution of regulatory code in the microbial world,
by Antonio Gomes, PhD, Memorial Sloan Kelttering Cancer Center, New York, USA.
He shall provide a good background in gene expression (an area that has been using machine learning, and shall be covered in the tutorial), HGT and microbial communities and explain how he models it (a nice opportunity to see imperative differences between "black" and "white" box models). See for instance for now: here.
The model is relatively simple, that he developed to simulate evolution of regulatory regions under HGT in microbial communities. Best contribution he can make is to show the audience the potential of using CI-like reasoning in biological problems.
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Therefore, do not lose the change to see possible new approach in your academic life!!
Evolutionary and Swarm Intelligence methods for Systems Biology
By Marco S. Nobile, PhD, Università Degli Studi di Milano- Bicocca, Italy
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On this talk, Marco Nobile shall present to you how techniques from computational intelligence, namely evolutionary computing and swarm intelligence, can be used in parameter estimation and similar tasks that raises in problems related to systems biology. Furthermore, he shall present as well how High-Performance computers (HPC) can be used on this situation to make it possible the heavy package of computations needed on this situation.
Biomedical Image Segmentation and Analysis using Machine Learning and Computational Intelligence Techniques
By Leonardo Rundo and Andrea Tangherloni, Ph.D. Student in Computer Science University of Milan-Bicocca, Department of Informatics, Systems and Communication (DISCo)
Nowadays, the amount of heterogeneous biomedical data is increasing more and more thanks to advancements in imaging acquisition modalities and High Throughput technologies. This huge information ensemble could overwhelm analytic capabilities concerning both physicians in their decision-making tasks and biologists in investigating live-cell dynamic processes.
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Computational approaches for medical and biological image analysis play a key role in radiology and laboratory applications. However, conventional Machine Learning and Computational techniques must be adapted and tailored to address the issues regarding biomedical images.
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In this webinar, the challenges and the characteristics of the most recent methods will be introduced and discussed by means of several practical applications, focusing on image segmentation and registration. Novel algorithms for computer-assisted medical image segmentation (especially in cancer imaging, dealing also with multimodal image processing) as well as for automated cell image analysis (related to cell detection for assessing cell-cycle progression) will be presented. To conclude, a recent Magnetic Resonance image enhancement method based on Genetic Algorithms will be briefly described.
Andrea Tangherloni
Leonardo Rundo
Confirmed!!!!
This one shall be in the tutorial section, 14:00-15:30, 31th October: http://cbic2017.org/Program
Timetable on the way!! click here for the current version
Confirmed!!!!
Confirmed!!!!
Follow the workshop from your computer (courtesy of Jonathan Karr):
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Participants from the 1st CIBio-CBIC;
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"Benfeitores" (participants from the crowdfounding campaign)
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Presenters
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Organizers
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Invited contributers
Confirmed!!!!
Correlated&Suggested from CBIC 2017 (main track)
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A hybrid algorithm for parameter estimation of the ghrelin dynamics based on in vivo data
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Applications of Artificial Intelligence in Healthcare and Medicine
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Avaliando Técnicas de Aprendizado Profundo para Detecção de Esquistossomose Mansoni em Imagens de Exames Parasitológicos
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Automated Detection of Segmental Glomerulosclerosis in Kidney Histopathology
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Aplicando Programação Genética na Geração de Classificadores de Sentimento
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Randomized Pattern Classiers for Epileptic Seizure Detection: A Critical Assessment
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Detecção de Anormalidades em Sons Pulmonares Baseada em FFT e Máquinas de Vetores Suporte
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Soft Biometrics Classication Using Denoising Convolutional Autoencoders and Support Vector Machines
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Detecção de Câncer de Pele com Redes Neurais Artificiais
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Cálculo de la importancia de características y evaluación de la calidad de proteínas en el
problema de discriminación de Decoys -
Uso de Técnicas de Mineração de Dados na Prevenção de Acidente Vascular Cerebral
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Inteligência Computacional para Estimação dos Requerimentos Energéticos em Gado Bovino
Ver para mais detalhes, como o horário: accepted papers, schedule.
Upload your webinar here.