Methods in molecular biology (Clifton, N.J.)
Jan 1, 2024
The greatest challenge in drug discovery remains the high rate of attrition across the different phases of the process, which cost the industry billions of dollars every year. While all phases remain crucial to ensure pharmaceutical-level safety, qua...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2024
Identification and optimization of small molecules that bind to and modulate protein function is a crucial step in the early stages of drug development. For decades, this process has benefitted greatly from the use of computational models that can pr...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2023
Leveraging existing resources in studied species to predict gene functions has the potential to rapidly expand understanding of annotated genes in other, less well-studied, species with assembled genomes. However, orthology is not a reliable predicto...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2023
After an examination of evidentiary or reference samples has been performed, the next step is DNA extraction. This crucial step allows for deoxyribonucleic acid (DNA) to be released from a substrate by use of a series of chemicals and allows the DNA ...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2023
Vaccine development is a complex and long process. It involves several steps, including computational studies, experimental analyses, animal model system studies, and clinical trials. This process can be accelerated by using in silico antigen screeni...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2023
Prediction of bacterial immunogens is a prerequisite for the process of vaccine development through reverse vaccinology. The application of in silico methods allows significant reduction in time and cost for the discovery of potential vaccine candida...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2023
Advanced computational approaches in artificial intelligence, such as machine learning, have been increasingly applied in life sciences and healthcare to analyze large-scale complex biological data, such as microbiome data. In this chapter, we descri...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2023
Homology modeling was long considered a method of choice in tertiary protein structure prediction. However, it used to provide models of acceptable quality only when templates with appreciable sequence identity with a target could be found. The thres...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2023
Discovering molecular biomarkers for predicting patient survival outcomes is an essential step toward improving prognosis and therapeutic decision-making in the treatment of severe diseases such as cancer. Due to the high-dimensionality nature of omi...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2023
Here we describe an approach that uses deep learning neural networks such as CNN and RNN to aggregate information from DNA sequence; physical, chemical, and structural properties of nucleotides; and omics data on histone modifications, methylation, c...