Improved machine learning models for predicting selective compounds.
Summary of "Improved machine learning models for predicting selective compounds."
No Summary Available
Department of Computer Science & Engineering and ‡College of Pharmacy, University of Minnesota , Twin Cities, Minneapolis, Minnesota 55455, United States.
This article was published in the following journal.
Name: Journal of chemical information and modeling
Medical and Biotech [MESH] Definitions
Change in learning in one situation due to prior learning in another situation. The transfer can be positive (with second learning improved by first) or negative (where the reverse holds).
Usually refers to the use of mathematical models in the prediction of learning to perform tasks based on the theory of probability applied to responses; it may also refer to the frequency of occurrence of the responses observed in the particular study.
Theoretical models which propose methods of learning or teaching as a basis or adjunct to changes in attitude or behavior. These educational interventions are usually applied in the fields of health and patient education but are not restricted to patient care.
Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment.
Compounds containing the hexamethylenebis(trimethylammonium) cation. Members of this group frequently act as antihypertensive agents and selective ganglionic blocking agents.
The identification of small potent compounds that selectively bind to the target under consideration with high affinities is a critical step toward successful drug discovery. However, there is still a...
Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typic...
Phospholipidosis is an adverse effect caused by numerous cationic amphiphilic drugs and can affect many cell types. It is characterized by the excess accumulation of phospholipids and is most reliably...
This paper is focused on modern approaches to machine learning, most of which are as yet used infrequently or not at all in chemoinformatics. Machine learning methods are characterized in terms of the...
In order to develop a computational method to rapidly evaluate transdermal peptides, we report approaches for predicting the transdermal activity of peptides on the basis of peptide sequence informati...
The course of the disease in female patients with metastatic mammary carcinoma can vary greatly. In this connection, the individual prognosis depends on a complex interaction of tumor- and...
Background: - Magnetic resonance imaging (MRI) uses a strong magnetic field and radio waves to take pictures of the brain. Some MRI studies suggest that this technique reveals bra...
This study aims to determine whether levodopa is effective in boosting learning and memory in healthy subjects and patients with dementia or Mild Cognitive Impairment. We also examine in...
Gliomas are one of the most challenging tumors to treat, because areas of the apparently normal brain contain microscopic deposits of glioma cells; indeed, these occult cells are known to...
This is a randomized controlled prospective study which assigned patient to receive manual CPR or automatic CPR machine use. The quality and efficacy between manual CPR and machine CPR wil...