Prescriptions

A computational method for drug sensitivity prediction of cancer cell lines based on various molecular information.

Determining sensitive drugs for a patient is one of the most critical problems in precision medicine. Using genomic profiles of the tumor and drug information can help in tailoring the most efficient treatment for a patient. In this paper, we proposed a classification machine learning approach that predicts the sensitive/resistant drugs for a cell line. It can be performed by using both drug and c...

ML-DTI: Mutual Learning Mechanism for Interpretable Drug-Target Interaction Prediction.

Deep learning (DL) provides opportunities for the identification of drug-target interactions (DTIs). The challenges of applying DL lie primarily with the lack of interpretability. Also, most of the existing DL-based methods formulate the drug and target encoder as two independent modules without considering the relationship between them. In this study, we propose a mutual learning mechanism to bri...

Ensemble Deep Learning Based on Multi-level Information Enhancement and Greedy Fuzzy Decision for Plant miRNA-lncRNA Interaction Prediction.

MicroRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are both non-coding RNAs (ncRNAs) and their interactions play important roles in biological proc...

High-Efficiency Machine Learning Method for Identifying Foodborne Disease Outbreaks and Confounding Factors.

The China National Center for Food Safety Risk Assessment (CFSA) uses the Foodborne Disease Monitoring and Reporting System (FDMRS) to monitor outbrea...

An Ensemble Learning-Based Method for Inferring Drug-Target Interactions Combining Protein Sequences and Drug Fingerprints.

Identifying the interactions of the drug-target is central to the cognate areas including drug discovery and drug reposition. Although the high-throug...

Intrinsic motivation in virtual assistant interaction for fostering spontaneous interactions.

With the growing utility of today's conversational virtual assistants, the importance of user motivation in human-artificial intelligence interactions...

Integrated Random Negative Sampling and Uncertainty Sampling in Active Learning Improve Clinical Drug Safety Drug-Drug Interaction Information Retrieval.

Clinical drug-drug interactions (DDIs) have been a major cause for not only medical error but also adverse drug events (ADEs). The published literatur...

Deep-learning based repurposing of FDA-approved drugs against dihydrofolate reductase and molecular dynamics study.

causes the fatal fungal bloodstream infection in humans called Candidiasis. Most of the species are resistant to the antifungals used to treat them....

Locomotor transitions in the potential energy landscape-dominated regime.

To traverse complex three-dimensional terrain with large obstacles, animals and robots must transition across different modes. However, the most mecha...

Tumor classification in automated breast ultrasound (ABUS) based on a modified extracting feature network.

People can get consistent Automated Breast Ultrasound (ABUS) images due to the imaging mechanism of scanning. Therefore, it has unique advantages in b...

Magnetically Actuated Drug Delivery Helical Microrobot with Magnetic Nanoparticle Retrieval Ability.

Therapeutic drug delivery microrobots capable of accurate targeting using an electromagnetic actuation (EMA) system are being developed. However, thes...

AutoDTI++: deep unsupervised learning for DTI prediction by autoencoders.

BACKGROUND: Drug-target interaction (DTI) plays a vital role in drug discovery. Identifying drug-target interactions related to wet-lab experiments ar...

Critical assessment of AI in drug discovery.

: Artificial Intelligence (AI) has become a component of our everyday lives, with applications ranging from recommendations on what to buy to the anal...

Sex-Specific Classification of Drug-Induced Torsade de Pointes Susceptibility Using Cardiac Simulations and Machine Learning.

Torsade de Pointes (TdP), a rare but lethal ventricular arrhythmia, is a toxic side effect of many drugs. To assess TdP risk, safety regulatory guidel...

Artificial intelligence to deep learning: machine intelligence approach for drug discovery.

Drug designing and development is an important area of research for pharmaceutical companies and chemical scientists. However, low efficacy, off-targe...

Application of network link prediction in drug discovery.

BACKGROUND: Technological and research advances have produced large volumes of biomedical data. When represented as a network (graph), these data beco...

Dielectric Engineered Two-Dimensional Neuromorphic Transistors.

Two-dimensional (2D) materials, which exhibit planar-wafer technique compatibility and pure electrically triggered communication, have established the...

A Novel Drug Repositioning Approach Based on Collaborative Metric Learning.

Computational drug repositioning, which is an efficient approach to find potential indications for drugs, has been used to increase the efficiency of ...

An Analytical Review of Computational Drug Repurposing.

Drug repurposing is a vital function in pharmaceutical fields and has gained popularity in recent years in both the pharmaceutical industry and resear...

The effect of facial features on facial anthropomorphic trustworthiness in social robots.

As the nature of human-robot relationships have become increasingly bound to shift from supervisor-machine to friend-companion, people have exhibited ...