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Phytochemical, antibacterial, antioxidant and cytoxicity investigation of .

Zeitschrift fur Naturforschung. C, Journal of biosciences
The phytochemical investigation of led to the isolation of 18 known compounds of which were four flavones, three anthraquinones, one phenyl propanoic derivative, five triterpenoids, four steroids and a mixture of glucose. Luteolin () and soranjidiol...

Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure.

Nature communications
Understanding the genetic regulatory code governing gene expression is an important challenge in molecular biology. However, how individual coding and non-coding regions of the gene regulatory structure interact and contribute to mRNA expression leve...

Deep-Learning Resources for Studying Glycan-Mediated Host-Microbe Interactions.

Cell host & microbe
Glycans, the most diverse biopolymer, are shaped by evolutionary pressures stemming from host-microbe interactions. Here, we present machine learning and bioinformatics methods to leverage the evolutionary information present in glycans to gain insig...

Predicting antimicrobial resistance using conserved genes.

PLoS computational biology
A growing number of studies are using machine learning models to accurately predict antimicrobial resistance (AMR) phenotypes from bacterial sequence data. Although these studies are showing promise, the models are typically trained using features de...

Gut microbiome-mediated epigenetic regulation of brain disorder and application of machine learning for multi-omics data analysis.

Genome
The gut-brain axis (GBA) is a biochemical link that connects the central nervous system (CNS) and enteric nervous system (ENS). Clinical and experimental evidence suggests gut microbiota as a key regulator of the GBA. Microbes living in the gut not o...

DeeplyEssential: a deep neural network for predicting essential genes in microbes.

BMC bioinformatics
BACKGROUND: Essential genes are those genes that are critical for the survival of an organism. The prediction of essential genes in bacteria can provide targets for the design of novel antibiotic compounds or antimicrobial strategies.

Assigning the Origin of Microbial Natural Products by Chemical Space Map and Machine Learning.

Biomolecules
Microbial natural products (NPs) are an important source of drugs, however, their structural diversity remains poorly understood. Here we used our recently reported MinHashed Atom Pair fingerprint with diameter of four bonds (MAP4), a fingerprint sui...

Keeping up with the genomes: efficient learning of our increasing knowledge of the tree of life.

BMC bioinformatics
BACKGROUND: It is a computational challenge for current metagenomic classifiers to keep up with the pace of training data generated from genome sequencing projects, such as the exponentially-growing NCBI RefSeq bacterial genome database. When new ref...

Sequence-enabled community-based microbial source tracking in surface waters using machine learning classification: A review.

Journal of microbiological methods
The development of Microbial Source Tracking (MST) technologies was borne out of necessity. This was largely due to the: 1) inadequacies of the fecal indicator bacterial paradigm, 2) fact that many fecal bacteria can survive and often grow in the env...

Microbial contamination and efficacy of disinfection procedures of companion robots in care homes.

PloS one
BACKGROUND: Paro and other robot animals can improve wellbeing for older adults and people with dementia, through reducing depression, agitation and medication use. However, nursing and care staff we contacted expressed infection control concerns. Li...