“This study introduces Cancer-Alterome, a literature-mined dataset that focuses on the regulatory events of an organism’s biological processes or clinical phenotypes caused by genetic alterations. It empowers investigation of cancer pathology, enabling tracking of relevant literature support.” “本研究介绍了Cancer-Alterome,这是一个通过文献挖掘得到的数据集,专注于研究生物体因遗传变异而导致的生物过程或临床表型的调控事件。它加强了癌症病理学的研究,并使得相关文献支持的追踪成为可能。” Behind the paper (https://www.nature.com/articles/s41597-024-03083-9): Cancer has long been a significant global health concern, posing a serious threatContinueContinue reading “《Cancer Alterome,文献资源如何有助于癌症病理学的精细化解释》”
Author Archives: hzaubionlp
Keywords: 辣堡,五分配
关键词如上,详情如图。
连钰珑师姐参与的“舆情预测”研究论文被接收
连钰珑师姐参与的“舆情与价格波动预测”研究工作最近被Computers and Electrical Engineering接收。 该工作主要通过人工设计舆情语义语料库、捕捉舆情对环境/市场/政策的响应,指导预测舆情走向和价格涨跌影响、预测蔬菜价格异常波动。小连师姐在其中提供Granger因果检验的算法实施,取得积极成效。 恭喜所有作者! Youzhu Li, Jinyu Yao, Jingjing Song, Yixin Feng, Heng Dong, Jingliang Zhao, Yulong Lian, Feng Shi, Jingbo Xia*. Investigation of Causal Public Opinion Indexes for Price Fluctuation in Vegetable Marketing. Computers and Electrical Engineering. 2024.
每一寸丈量的土地都不会辜负——《追光者》。
新学期,元气满满的周六组会
Nature portfolio 将课题组的Cancer-Alterome研究工作归入“Tumor biomarkers”主题
请访问https://www.nature.com/subjects/tumour-biomarkers,获得和我们主题相同的其他研究。
DGGAT paper is indexed in IEEE
https://ieeexplore.ieee.org/abstract/document/10385796 Integrating Multi-omics Data into A Gated Graph Convolutional Networks for Identifying Cancer Driver Genes and Function Modules Publisher: IEEE Qianqian Peng; Zhihan He; Shichao Liu; Xinzhi Yao; Jingbo Xia Abstract: The identification of cancer driver genes is important for better understanding the hallmarks of cancer and developing precision therapies. Though the integration of multiomics and protein-protein interaction (PPI) dataContinueContinue reading “DGGAT paper is indexed in IEEE”
美食和BLAH8黑客松
姚和子铭参加了日本DBCLS举办的BLAH 8 黑客松,分别围绕“Rice-Alterome的LLM标注”和“LLM下的语料主题迁移”展开学术黑客松交流。 主要吃了这些美食。
冬至后研讨+忘贴的墙报
周六组会——Thesis进展,5分钟Briefing。 实验室年会——墙报
彭钱钱视频讲解DGGAT模型 ——《多组学和门控图卷积网络用于驱动基因和功能模块的预测》
❏ DGGAT模型 (多组学和门控图卷积网络用于驱动基因和功能模块的预测)时长: 10’01″/讲解: 英文/字幕:英文 https://youtu.be/R0HzJzFVxQ4 Youtube video DGGAT in BIBM, Istanbul, 2023(Algorithmic description of DGGAT model) B站镜像: Bilibili video Narrator: Qianqian Peng (彭钱钱)