AI Medical Compendium Journal:
Methods in molecular biology (Clifton, N.J.)

Showing 81 to 90 of 269 articles

A Machine Learning-Based Approach Using Multi-omics Data to Predict Metabolic Pathways.

Methods in molecular biology (Clifton, N.J.)
The integrative method approaches are continuously evolving to provide accurate insights from the data that is received through experimentation on various biological systems. Multi-omics data can be integrated with predictive machine learning algorit...

Computational Methods and Deep Learning for Elucidating Protein Interaction Networks.

Methods in molecular biology (Clifton, N.J.)
Protein interactions play a critical role in all biological processes, but experimental identification of protein interactions is a time- and resource-intensive process. The advances in next-generation sequencing and multi-omics technologies have gre...

Synthetic Biology Meets Machine Learning.

Methods in molecular biology (Clifton, N.J.)
This chapter outlines the myriad applications of machine learning (ML) in synthetic biology, specifically in engineering cell and protein activity, and metabolic pathways. Though by no means comprehensive, the chapter highlights several prominent com...

Design and Construction of Unmanned Ground Vehicles for Sub-canopy Plant Phenotyping.

Methods in molecular biology (Clifton, N.J.)
Unmanned ground vehicles can capture a sub-canopy perspective for plant phenotyping, but their design and construction can be a challenge for scientists unfamiliar with robotics. Here we describe the necessary components and provide guidelines for de...

A Deep Learning Approach to Identify Chest Computed Tomography Features for Prediction of SARS-CoV-2 Infection Outcomes.

Methods in molecular biology (Clifton, N.J.)
There is still an urgent need to develop effective treatments to help minimize the cases of severe COVID-19. A number of tools have now been developed and applied to address these issues, such as the use of non-contrast chest computed tomography (CT)...

BioBERT and Similar Approaches for Relation Extraction.

Methods in molecular biology (Clifton, N.J.)
In biomedicine, facts about relations between entities (disease, gene, drug, etc.) are hidden in the large trove of 30 million scientific publications. The curated information is proven to play an important role in various applications such as drug r...

A Hybrid Protocol for Identifying Comorbidity-Based Potential Drugs for COVID-19 Using Biomedical Literature Mining, Network Analysis, and Deep Learning.

Methods in molecular biology (Clifton, N.J.)
Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) has spread on an unprecedented scale around the globe. Despite of 141,975 published papers on COVID-19 and several hundreds of new studies carri...

Text Mining and Machine Learning Protocol for Extracting Human-Related Protein Phosphorylation Information from PubMed.

Methods in molecular biology (Clifton, N.J.)
In the modern health care research, protein phosphorylation has gained an enormous attention from the researchers across the globe and requires automated approaches to process a huge volume of data on proteins and their modifications at the cellular ...

Combining Literature Mining and Machine Learning for Predicting Biomedical Discoveries.

Methods in molecular biology (Clifton, N.J.)
The major outcomes and insights of scientific research and clinical study end up in the form of publication or clinical record in an unstructured text format. Due to advancements in biomedical research, the growth of published literature is getting t...

Biomedical Literature Mining for Repurposing Laboratory Tests.

Methods in molecular biology (Clifton, N.J.)
Epidemiological studies identifying biological markers of disease state are valuable, but can be time-consuming, expensive, and require extensive intuition and expertise. Furthermore, not all hypothesized markers will be borne out in a study, suggest...