Discovering Drug-Target Interaction Knowledge from Biomedical Literature

09/27/2021
by   Yutai Hou, et al.
0

The Interaction between Drugs and Targets (DTI) in human body plays a crucial role in biomedical science and applications. As millions of papers come out every year in the biomedical domain, automatically discovering DTI knowledge from biomedical literature, which are usually triplets about drugs, targets and their interaction, becomes an urgent demand in the industry. Existing methods of discovering biological knowledge are mainly extractive approaches that often require detailed annotations (e.g., all mentions of biological entities, relations between every two entity mentions, etc.). However, it is difficult and costly to obtain sufficient annotations due to the requirement of expert knowledge from biomedical domains. To overcome these difficulties, we explore the first end-to-end solution for this task by using generative approaches. We regard the DTI triplets as a sequence and use a Transformer-based model to directly generate them without using the detailed annotations of entities and relations. Further, we propose a semi-supervised method, which leverages the aforementioned end-to-end model to filter unlabeled literature and label them. Experimental results show that our method significantly outperforms extractive baselines on DTI discovery. We also create a dataset, KD-DTI, to advance this task and will release it to the community.

READ FULL TEXT
research
01/31/2018

Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations

We propose the Onto2Vec method, an approach to learn feature vectors for...
research
01/28/2021

Heterogeneous Graph based Deep Learning for Biomedical Network Link Prediction

Multi-scale biomedical knowledge networks are expanding with emerging ex...
research
09/04/2023

Into the Single Cell Multiverse: an End-to-End Dataset for Procedural Knowledge Extraction in Biomedical Texts

Many of the most commonly explored natural language processing (NLP) inf...
research
04/23/2020

MolTrans: Molecular Interaction Transformer for Drug Target Interaction Prediction

Drug target interaction (DTI) prediction is a foundational task for in s...
research
10/26/2022

BioNLI: Generating a Biomedical NLI Dataset Using Lexico-semantic Constraints for Adversarial Examples

Natural language inference (NLI) is critical for complex decision-making...
research
03/19/2021

Biomedical Convergence Facilitated by the Emergence of Technological and Informatic Capabilities

We analyzed Medical Subject Headings (MeSH) from 21.6 million research a...
research
04/27/2023

BactInt: A domain driven transfer learning approach and a corpus for extracting inter-bacterial interactions from biomedical text

The community of different types of microbes present in a biological nic...

Please sign up or login with your details

Forgot password? Click here to reset