Methods in molecular biology (Clifton, N.J.)
Jan 1, 2025
The recent advancements in machine learning and the new availability of large chemical datasets made the development of tools and protocols for computational chemistry a topic of high interest. In this chapter a standard procedure to develop Quantita...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2025
In this chapter, we discuss the potential application of Restricted Boltzmann machines (RBM) to model sequence families of structured RNA molecules. RBMs are a simple two-layer machine learning model able to capture intricate sequence dependencies in...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2025
Fundamental to the diverse biological functions of RNA are its 3D structure and conformational flexibility, which enable single sequences to adopt a variety of distinct 3D states. Currently, computational RNA design tasks are often posed as inverse p...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2025
Machine learning algorithms, and in particular deep learning approaches, have recently garnered attention in the field of molecular biology due to remarkable results. In this chapter, we describe machine learning approaches specifically developed for...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2025
Three-dimensional (3D) chromatin interactions, such as enhancer-promoter interactions (EPIs), loops, topologically associating domains (TADs), and A/B compartments, play critical roles in a wide range of cellular processes by regulating gene expressi...
Bioinformatics (Oxford, England)
Dec 26, 2024
MOTIVATION: The knowledge of protein stability upon residue variation is an important step for functional protein design and for understanding how protein variants can promote disease onset. Computational methods are important to complement experimen...
Bioinformatics (Oxford, England)
Dec 26, 2024
MOTIVATION: Multiple sequence alignments (MSAs) are extensively used in biology, from phylogenetic reconstruction to structure and function prediction. Here, we suggest an out-of-the-box approach for the inference of MSAs, which relies on algorithms ...
Bioinformatics (Oxford, England)
Dec 26, 2024
MOTIVATION: Due to the breakthrough in protein structure prediction by AlphaFold, the scientific community has access to 200 million predicted protein structures with near-atomic accuracy from the AlphaFold protein structure DataBase (AFDB), covering...
Bioinformatics (Oxford, England)
Dec 26, 2024
MOTIVATION: Peptides and their derivatives hold potential as therapeutic agents. The rising interest in developing peptide drugs is evidenced by increasing approval rates by the FDA of USA. To identify the most potential peptides, study on peptide-pr...
Cell systems
Dec 18, 2024
The adaptive immune system holds invaluable information on past and present immune responses in the form of B and TÂ cell receptor sequences, but we are limited in our ability to decode this information. Machine learning approaches are under active in...