Titlebook: Bioinformatics and Biomedical Engineering; 5th International Wo Ignacio Rojas,Francisco Ortu?o Conference proceedings 2017 Springer Interna

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Im Angebot: Spezielle Verteilungenl approach uses single point measurement in CIEL*a*b* color space. On the other hand the image acquisition by digital cameras allows to evaluate spatial statistic, in RGB color space. The reliability of the camera color accuracy as well as the software and method description for the automatic color

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Markus Oestreich,Oliver Rombergtection of DDIs bears a high cost. Machine learning-based computational approaches can be the assistance of experimental approaches. Utilizing pre-market drug properties (e.g. side effects), they are able to predict DDIs on a large scale before drugs enter the market. However, none of them can predi

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Unsere erste Bilanz, die Massenbilanz,s known as transcriptomic age. This differs from chronological age which is measured as the time that an individual has lived since their date of birth. Transcriptomic age can be older or younger than an individual’s chronological age. At present, studies have focused on using transcriptomic data to

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,Hauptsache Haupts?tze - Der 1. Hauptsatz,r accurate and . classification of pathogenic viruses. For this study, we curated genomic sequences of selected viral pathogens from the virus pathogen database and analysis resource corpus. The viral genomes were encoded using the first to seventh order FCGRs so as to produce training and testing g

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Thermische Zustandsgleichungen,e, especially among youth. This paper analyses the functionalities and explores gamification elements of the existing blood donation apps in the mobile market. A search in Google Play, Apple Apps store, Blackberry App World, and Windows Mobile App store was performed to select 10 gamified BD apps wi

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Unsere erste Bilanz, die Massenbilanz,availability of medical data in electronic form. It is time to provide physicians with near-to-the-clinical-practice and effective tools to spread this important technological innovation. In this paper, we describe RISK, a web service that implements a multiple kernel learning approach for predictin

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