Ad
related to: machine-learning approaches in drug discovery: methods and applications
Search results
Results from the Health.Zone Content Network
t. e. Machine learning in bioinformatics is the application of machine learning algorithms to bioinformatics, [1] including genomics, proteomics, microarrays, systems biology, evolution, and text mining. [2] [3] Prior to the emergence of machine learning, bioinformatics algorithms had to be programmed by hand; for problems such as protein ...
The following learning method can be any of the already mentioned machine learning methods, e.g. support vector machines. An alternative approach uses multiple-instance learning by encoding molecules as sets of data instances, each of which represents a possible molecular conformation. A label or response is assigned to each set corresponding ...
Application to drug discovery. Virtual screening is a very useful application when it comes to identifying hit molecules as a beginning for medicinal chemistry. As the virtual screening approach begins to become a more vital and substantial technique within the medicinal chemistry industry the approach has had an expeditious increase.
Drug discovery. In the fields of medicine, biotechnology and pharmacology, drug discovery is the process by which new candidate medications are discovered. [1] Historically, drugs were discovered by identifying the active ingredient from traditional remedies or by serendipitous discovery, as with penicillin. More recently, chemical libraries of ...
Biomedical data science. Biomedical data science is a multidisciplinary field which leverages large volumes of data to promote biomedical innovation and discovery. Biomedical data science draws from various fields including Biostatistics, Biomedical informatics, and machine learning, with the goal of understanding biological and medical data.
The primary goal of bioinformatics is to increase the understanding of biological processes. What sets it apart from other approaches is its focus on developing and applying computationally intensive techniques to achieve this goal. Examples include: pattern recognition, data mining, machine learning algorithms, and visualization.
Machine learning and data mining often employ the same methods and overlap significantly, but while machine learning focuses on prediction, based on known properties learned from the training data, data mining focuses on the discovery of (previously) unknown properties in the data (this is the analysis step of knowledge discovery in databases).
Regina Barzilay (born 1970) is an Israeli-American computer scientist. She is a professor at the Massachusetts Institute of Technology and a faculty lead for artificial intelligence at the MIT Jameel Clinic. Her research interests are in natural language processing and applications of deep learning to chemistry and oncology .
Ad
related to: machine-learning approaches in drug discovery: methods and applications