COVID-19Base: A knowledgebase to explore biomedical entities related to COVID-19
원문 초록
We are presenting COVID-19Base, a knowledgebase highlighting the biomedical entities related to COVID-19 disease based on literature mining. To develop COVID-19Base, we mine the information from publicly available scientific literature and related public resources. We considered seven topic-specific dictionaries, including human genes, human miRNAs, human lncRNAs, diseases, Protein Databank, drugs, and drug side effects, are integrated to mine all scientific evidence related to COVID-19. We have employed an automated literature mining and labeling system through a novel approach to measure the effectiveness of drugs against diseases based on natural language processing, sentiment analysis, and deep learning. To the best of our knowledge, this is the first knowledgebase dedicated to COVID-19, which integrates such large variety of related biomedical entities through literature mining. Proper investigation of the mined biomedical entities along with the identified interactions among those, reported in COVID-19Base, would help the research community to discover possible ways for the therapeutic treatment of COVID-19.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Understanding and Tackling Label Errors in Individual-Level Nature Language Understanding
DCR: Quantifying Data Contamination in LLMs Evaluation
AI Wizards at CheckThat! 2025: Enhancing Transformer-Based Embeddings with Sentiment for Subjectivity Detection in News Articles
Characterizing Linguistic Shifts in Croatian News via Diachronic Word Embeddings
CAtCh: Cognitive Assessment through Cookie Thief
Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning
토론
이 논문과 연결된 포럼 글이 아직 없습니다.