HeteroKGRep: Heterogeneous Knowledge Graph based Drug Repositioning.

The process of developing new drugs is both time-consuming and costly, often taking over a decade and billions of dollars to obtain regulatory approval. Additionally, the complexity of patent protection for novel compounds presents challenges for pharmaceutical innovation. Drug repositioning offers an alternative strategy to uncover new therapeutic uses for existing medicines.

Biofilm marker discovery with cloud-based dockerized metagenomics analysis of microbial communities.

In an environment, microbes often work in communities to achieve most of their essential functions, including the production of essential nutrients. Microbial biofilms are communities of microbes that attach to a nonliving or living surface by embedding themselves into a self-secreted matrix of extracellular polymeric substances. These communities work together to enhance their colonization of surfaces, produce essential nutrients, and achieve their essential functions for growth and survival.

Sub-clustering based recommendation system for stroke patient: Identification of a specific drug class for a given patient.

Stroke is one of the leading causes of death worldwide. Previous studies have explored machine learning techniques for early detection of stroke patients using content-based recommendation systems. However, these models often struggle with timely detection of medications, which can be critical for patient management and decision-making regarding the prescription of new drugs.

Molecular analysis of the blood meals and bacterial communities of bed bugs (Cimex lectularius L.) to assess interactions with alternative hosts.

Common bed bugs (Cimex lectularius L.) are hematophagous pests present in urban environments across the globe. It is widely established that they have a strong host preference for humans.

Assessment of vector-host-pathogen relationships using data mining and machine learning.

Infectious diseases, including vector-borne diseases transmitted by arthropods, are a leading cause of morbidity and mortality worldwide. In the era of big data, addressing broad-scale, fundamental questions regarding the complex dynamics of these diseases will increasingly require the integration of diverse datasets to produce new biological knowledge. This review provides a current snapshot of the systematic assessment of the relationships between microbial pathogens, arthropod vectors and mammalian hosts using data mining and machine learning.

Body lice and bed bug co-infestation in an emergency department patient, Ohio, USA.

Body lice and bed bugs are hematophagous insects that parasitize humans. Body lice are established vectors of several bacterial pathogens (e.g.

Microbiome Differences Between Human Head and Body Lice Ecotypes Revealed by 16S RRNA Gene Amplicon Sequencing.

Human head lice and body lice () are neglected ectoparasites. Head lice continue to be prevalent in children worldwide, and insecticide resistance in these insects has complicated their treatment. Meanwhile, body lice, which are most common in the developing world, are resurging among marginalized populations in developed nations.