Measurement of Ability in Adaptive Learning and Assessment Systems when Learners Use On-Demand Hints.

Adaptive learning and assessment systems support learners in acquiring knowledge and skills in a particular domain. The learners' progress is monitored through them solving items matching their level and aiming at specific learning goals. Scaffolding and providing learners with hints are powerful tools in helping the learning process.

Self-Directed Learning Favors Local, Rather Than Global, Uncertainty.

Collecting (or "sampling") information that one expects to be useful is a powerful way to facilitate learning. However, relatively little is known about how people decide which information is worth sampling over the course of learning. We describe several alternative models of how people might decide to collect a piece of information inspired by "active learning" research in machine learning.

SIRT3 substrate specificity determined by peptide arrays and machine learning.

Accumulating evidence suggests that reversible protein acetylation may be a major regulatory mechanism that rivals phosphorylation. With the recent cataloging of thousands of acetylation sites on hundreds of proteins comes the challenge of identifying the acetyltransferases and deacetylases that regulate acetylation levels. Sirtuins are a conserved family of NAD(+)-dependent protein deacetylases that are implicated in genome maintenance, metabolism, cell survival, and lifespan.

ABNER: an open source tool for automatically tagging genes, proteins and other entity names in text.

ABNER (A Biomedical Named Entity Recognizer) is an open source software tool for molecular biology text mining. At its core is a machine learning system using conditional random fields with a variety of orthographic and contextual features. The latest version is 1.