Multitype Perception Method for Drug-Target Interaction Prediction.

With the growing popularity of artificial intelligence in drug discovery, many deep-learning technologies have been used to automatically predict unknown drug-target interactions (DTIs). A unique challenge in using these technologies to predict DTI is fully exploiting the knowledge diversity across different interaction types, such as drug-drug, drug-target, drug-enzyme, drug-path, and drug-structure types. Unfortunately, existing methods tend to learn the specifical knowledge on each interaction type and they usually ignore the knowledge diversity across different interaction types.

Enhanced post-quantum key escrow system for supervised data conflict of interest based on consortium blockchain.

Consortium blockchains offer privacy for members while allowing supervision peers access to on-chain data under certain circumstances. However, current key escrow schemes rely on vulnerable traditional asymmetric encryption/decryption algorithms. To address this issue, we have designed and implemented an enhanced post-quantum key escrow system for consortium blockchains.

Community-based rumor blocking maximization in social networks: Algorithms and analysis.

Social networks provide us a convenient platform to communicate and share information or ideas with each other, but it also causes many negative effects at the same time, such as, the spread of misinformation or rumor in social networks may cause public panic and even serious economic or political crisis. In this paper, we propose a Community-based Rumor Blocking Problem (CRBMP), i.e.