Monthly Archives: April 2021

Here, enrRiceTrait is a new tool for rice trait ontology. To present the enrichment, gene-trait association results are based on text mining and available data bases, while the traits are normalized by RTO 1.0, a newly developed rice trait ontology. https://www.youtube.com/watch?v=Fqjibzn7IxY Narrator: Yun Liu (Video released in Apr, 2021). Alternatively, watch the video here. ToContinueContinue reading “The lab is releasing a new video about enrRiceTrait”

We are happy to have Dr. Anastasia Krithara from National Center for Scientific Research “Demokritos” virtually visited us and give a wonderful online talk, entitled as “iASiS Open Data Graph: Automated Semantic Integration of Disease-Specific Knowledge”. http://coi.hzau.edu.cn/info/1023/7518.htm

A hill called Tuan Shan 团山, which is close to the East lake.

This work shows how AGAC serves for LOF/GOF mutation retrieval and Gene–Disease Association prediction. Link to the paper. Abstract Bridging heterogeneous mutation data fills in the gap between various data categories and propels discovery of disease-related genes. It is known that genome-wide association study (GWAS) infers significant mutation associations that link genotype and phenotype. However, due toContinueContinue reading ““AGAC on mutation information bridging” is published online. Congrats!”

Congratulations to Xuan for the acceptance of the “pathway enrichment” paper. In this research, Xuan developed a set of new metrics to evaluate the effective of pathway enrichment in terms of text mined vital gene set. This research reflect an interesting view, from which BioNLPers could observe how the literature-mined entities contribute to the downstreamContinueContinue reading “Congrats Xuan for an paper-acceptance in JMIR medical informatics”