The biomedical relationship corpus of the BioRED track at the BioCreative VIII challenge and workshop.

The automatic recognition of biomedical relationships is an important step in the semantic understanding of the information contained in the unstructured text of the published literature. The BioRED track at BioCreative VIII aimed to foster the development of such methods by providing the participants the BioRED-BC8 corpus, a collection of 1000 PubMed documents manually curated for diseases, gene/proteins, chemicals, cell lines, gene variants, and species, as well as pairwise relationships between them which are disease-gene, chemical-gene, disease-variant, gene-gene, chemical-disease, chemical-chemical, chemical-variant, and variant-variant. Furthermore, relationships are categorized into the following semantic categories: positive correlation, negative correlation, binding, conversion, drug interaction, comparison, cotreatment, and association.

Next generation multiplexing for digital PCR using a novel melt-based hairpin probe design.

Digital PCR (dPCR) is a powerful tool for research and diagnostic applications that require absolute quantification of target molecules or detection of rare events, but the number of nucleic acid targets that can be distinguished within an assay has limited its usefulness. For most dPCR systems, one target is detected per optical channel and the total number of targets is limited by the number of optical channels on the platform. Higher-order multiplexing has the potential to dramatically increase the usefulness of dPCR, especially in scenarios with limited sample.

Amide- and bis-amide-linked highly potent and broadly active antifungal agents for the treatment of invasive fungal infections- towards the discovery of pre-clinical development candidate FC12406.

Most fungal infections are common, localized to skin or mucosal surfaces and can be treated effectively with topical antifungal agents. However, while invasive fungal infections (IFIs) are uncommon, they are very difficult to control medically, and are associated with high mortality rates. We have previously described highly potent bis-guanidine-containing heteroaryl-linked antifungal agents, and were interested in expanding the range of agents to novel series so as to reduce the degree of aromaticity (with a view to making the compounds more drug-like), and provide broadly active high potency derivatives.

NLM-Chem-BC7: manually annotated full-text resources for chemical entity annotation and indexing in biomedical articles.

The automatic recognition of chemical names and their corresponding database identifiers in biomedical text is an important first step for many downstream text-mining applications. The task is even more challenging when considering the identification of these entities in the article's full text and, furthermore, the identification of candidate substances for that article's metadata [Medical Subject Heading (MeSH) article indexing]. The National Library of Medicine (NLM)-Chem track at BioCreative VII aimed to foster the development of algorithms that can predict with high quality the chemical entities in the biomedical literature and further identify the chemical substances that are candidates for article indexing.