Highlight | iPhone App - A fun way to learn more about people nearby s Free iPhone app! Your Fitbit One is always tracking, even when the display is asleep. Press the button to view your stats. Your flower will grow and shrink, depending on how active you've been recently. Calories burned includes resting calories and calories from activity. The activity stats shown on your tracker reset at midnight. To track your sleep, press and hold the button on your tracker until you see the stopwatch. Press and hold the same button when you are awake to end your sleep recording. Use Silent Alarms to wake from sleep without disturbing your partner. Your One gently vibrates on your wrist to silently wake you. Your Fitbit One contains a rechargeable battery. When plugged into the Charging Cable, it takes about 2 hours for your tracker to be fully charged. Your activity information is sent to your computer when your tracker is within 20 feet of the plugged-in Wireless Sync Dongle Syncing happens automatically. For a full list of supported devices, visit: steps
Audacity: Free Audio Editor and Recorder INDI: inferring novel drug interactions INDI is a large scale method for prediction of pharmacokinetic (Cytochrome P450-related) and pharmacodynamic drug-drug interactions. INDI is based on the observation that similar pairs of drugs tend to form similar interactions, and utilizes multiple drug-drug similarity measures for the prediction task. Disclaimer: The results displayed on this web page are predicted drug-drug interactions. Freely available sources for known drug interactions include DrugBank and www.drugs.com How to cite us:
CX for iPhone, iPod touch and iPad on the iTunes App Store openbiomind - A toolkit for analysis of gene expression, SNP and other biological datasets using advanced machine learning techniques OpenBiomind is a toolkit for analysis of gene expression, SNP and other biological datasets using advanced machine learning and pattern mining techniques, and includes traditional clustering, hybrid clustering, and other techniques. OpenBiomind is modular and command-line driven. Components communicate via standardized file formats. OpenBiomind commands cover: • Dataset enhancement, with information extracted from gene and protein ontologies, as well as other dataset treatments/transformations (such as feature selection and creation of validation folds) • Multiple classification model generation, for a given dataset using several modalities of GP. • Important Feature computation • Clustering using direct expression or MOBRA/MUTIC transformations • Cluster visualization (conventional, raster,color-coded) • Graph vizualization showing various inter-relationships among features: co-expression, co-occurrence and utility and differentiation ranks
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