This paper proposes an ensemble approach based on data partitioning for large-scale DNA motif analysis. Motif prediction using genome-scale dataset is challenging due to high time and space complexity ...

For the first phase, we use a dataset of pairs of observations with captions (i.e., messages from the game) collected by agents trained with reinforcement learning to maximize the game score. We ...

GlobalData has access to a proprietary data set containing invoice data from over 2,600 healthcare institutions in the US and is therefore able to use estimations of a company’s revenue and growth to ...

Another nice technical innovation: Motif uses WebAssembly to allow users to work with local datasets in the browser without having to send any of their data to the company’s servers.

A new benchmark dataset was established and used for training and testing our motif localization model. Firstly, 334 homo-dimers, which were verified by nuclear magnetic resonance (NMR), mutagenesis ...

I'm running a motif analysis on a human multiome dataset which I've called 'sconly'. This analysis run perfectly well last week, but for some reason now it keeps failing. I'm pasting below what I had ...

The thresholds for statistical significance were adj P < 0.05 and deltaBeta < -0.05. We used the human reference genome annotation dataset and human binding motif dataset, which uses the position ...

Motif Bio plc (AIM/NASDAQ: MTFB), a clinical-stage biopharmaceutical company specialising in developing novel antibiotics, today reported that new iclaprim data were presented at the American Society ...