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Network Link Prediction in Drug Discovery

A recent study carried out a comparative evaluation of network-based machine learning algorithms for network link prediction in the application […]

Real-World Outcomes of Razumab Treatment for Chorioretinal Diseases

A recent study aimed to assess the safety of intravitreal ranibizumab biosimilar molecule (Razumab) treatment for chorioretinal diseases under real-world […]

Bootstrapped Machine Learning for Characterising Compounds in Drug Discovery

Researchers from Purdue University have created a new method of bootstrapped machine learning applied to the tandem mass spectrometry process, […]

Real-world Effectiveness of HIV Treatment

A recent study aimed to evaluate the outcomes of standard-of-care triple therapy versus two-drug treatment for HIV, following the observation […]

Real-world Effectiveness of Candesartan as Migraine Treatment

Clinical trials are used to determine the efficacy of a drug in patients. However, effective clinical trials that have a large […]

Rapid ML Screening Identifies Potential Drug Compounds For SARS-CoV-2

At the time of writing, there have been 137 million cases and nearly 3 million deaths from COVID-19. Although some targets […]

Epigenetic Target Fishing Using ML

Epigenetic targets are of significant importance in drug discovery research, and there is increasing availability of chemogenomic data related to […]

Identifying the Bioactive Compounds in Ginger for Treatment in Colon Cancer

An article, published in BioData Mining, aimed to identify the bioactive compounds in ginger as a treatment for colon cancer […]

Standardised Data Structures in Rare Diseases

A recent study published in Clinical and Translational Science has outlined a method to develop standardised data structures based on […]

WELM-SURF: Predicting Drug-Target Interactions

Predicting novel drug-target interactions plays an important role in identifying new drug candidates and finding new proteins to target. An […]