Author Archives: hzaubionlp

We are happy to release a video which introduces AGAC corpus and its application in mutation type discovery. A recent case study in gene-disease association discovery in AD is as well introduced. https://youtu.be/YlzxtMkaYQk Narrator: Yuxing Wang Alternatively, visit the video via this link. To visit the whole AGAC page, please click here.

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”

Let’s congrats the final publication of the paper “Key phrase Extraction by Improving TextRank with an Integration of Word Embedding and Syntactic Information” in Recent Advances in Computer Science and Communications, 2021, 14(9): 2987-2993. It was a work done by college grade-1 students years ago. Never easy. Congrats!

A lot of BEEF and FIRE.

Nice work. It is fun to attend BLAH7 in a virtual way. https://blah7.linkedannotation.org/program We are also curious to see how AGAC annotation would contribute for the knowledge discovery by unveiling entity and relations from covid-19 literature. More about the work: https://hzaubionlp.com/agac-on-covid-19-literature/ Thank Yuxing who gave three rounds of plenary talks during the five days hackathon.