SIENA: Semi-automatic semantic enhancement of datasets using concept recognition.

Background: The amount of available data, which can facilitate answering scientific research questions, is growing. However, the different formats of published data are expanding as well, creating a serious challenge when multiple datasets need to be integrated for answering a question.

Results: This paper presents a semi-automated framework that provides semantic enhancement of biomedical data, specifically gene datasets.

ADDI: Recommending alternatives for drug-drug interactions with negative health effects.

Investigating the interactions among various drugs is an indispensable issue in the field of computational biology. Scientific literature represents a rich source for the retrieval of knowledge about the interactions between drugs. Predicting drug-drug interaction (DDI) types will help biologists to evade hazardous drug interactions and support them in discovering potential alternatives that increase therapeutic efficacy and reduce toxicity.

An Ecological Momentary Intervention for weight loss and healthy eating via smartphone and Internet: study protocol for a randomised controlled trial.

Background: Long-term weight loss maintenance is difficult to achieve. Effectiveness of obesity interventions could be increased by providing extended treatment, and by focusing on person-environment interactions. Ecological Momentary Intervention (EMI) can account for these two factors by allowing an indefinite extension of a treatment protocol in everyday life.

ARWAR: A network approach for predicting Adverse Drug Reactions.

Predicting novel drug side-effects, or Adverse Drug Reactions (ADRs), plays an important role in the drug discovery process. Existing methods consider mainly the chemical and biological characteristics of each drug individually, thereby neglecting information hidden in the relationships among drugs. Complementary to the existing individual methods, in this paper, we propose a novel network approach for ADR prediction that is called Augmented Random-WAlk with Restarts (ARWAR).

A combined ion source for fast switching between electrospray and matrix-assisted laser desorption/ionization in Fourier transform ion cyclotron resonance mass spectrometry.

A new ion source has been developed for Fourier transform ion cyclotron resonance mass spectrometry (FTICRMS) that enables quick changes between matrix-assisted laser desorption/ionization (MALDI) and electrospray ionization (ESI) modes. When operating as an ESI source, the sample solution is sprayed through an angled nebulizer. The generated ions pass through a glass capillary followed by a skimmer and three sequential hexapole ion guides.