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

Showing 71 to 80 of 269 articles

Deep Learning on Chromatin Accessibility.

Methods in molecular biology (Clifton, N.J.)
DNA accessibility has been a powerful tool in locating active regulatory elements in a cell type, but dissecting the combinatorial logic within these regulatory elements has been a continued challenge in the field. Deep learning models have been show...

3D Visualization of Microtubules in Epidermal Pavement Cells.

Methods in molecular biology (Clifton, N.J.)
The plant cytoskeleton is instrumental in cellular processes such as cell growth, differentiation, and immune response. Microtubules, in particular, play a crucial role in morphogenesis by governing the deposition of plant cell wall polysaccharides a...

A Guide to MethylationToActivity: A Deep Learning Framework That Reveals Promoter Activity Landscapes from DNA Methylomes in Individual Tumors.

Methods in molecular biology (Clifton, N.J.)
Genome-wide DNA methylomes have contributed greatly to tumor detection and subclassification. However, interpreting the biological impact of the DNA methylome at the individual gene level remains a challenge. MethylationToActivity (M2A) is a pipeline...

Applying Machine Learning to Classify the Origins of Gene Duplications.

Methods in molecular biology (Clifton, N.J.)
Nearly all lineages of land plants have experienced at least one whole-genome duplication (WGD) in their history. The legacy of these ancient WGDs is still observable in the diploidized genomes of extant plants. Genes originating from WGD-paleologs-c...

ResidualBind: Uncovering Sequence-Structure Preferences of RNA-Binding Proteins with Deep Neural Networks.

Methods in molecular biology (Clifton, N.J.)
Deep neural networks have demonstrated improved performance at predicting sequence specificities of DNA- and RNA-binding proteins. However, it remains unclear why they perform better than previous methods that rely on k-mers and position weight matri...

Live-Cell Labeling and Artificial Intelligence Approaches for High-Resolution XYZT Imaging of Cytoskeletal Dynamics During Collective Cell Migration.

Methods in molecular biology (Clifton, N.J.)
Collective cell migration is crucial for a variety of pathophysiological processes including embryonic development, wound healing, carcinoma invasion, and sprouting angiogenesis. The behavior of leading and following cells during migration is highly ...

A Primer on Deep Learning-Based Cellular Image Classification of Changes in the Spatial Distribution of the Golgi Apparatus After Experimental Manipulation.

Methods in molecular biology (Clifton, N.J.)
The visual classification of cell images according to differences in the spatial patterns of subcellular structure is an important methodology in cell and developmental biology. Experimental perturbation of cell function can induce changes in the spa...

Differential Expression, Functional and Machine Learning Analysis of High-Throughput -Omics Data Using Open-Source Tools.

Methods in molecular biology (Clifton, N.J.)
Today, -omics analyses, including the systematic cataloging of messenger RNA and microRNA sequences or DNA methylation patterns in a cell population, organ or tissue sample, allow for an unbiased, comprehensive genome-level analysis of complex diseas...

How to Design Peptides.

Methods in molecular biology (Clifton, N.J.)
Novel design of proteins to target receptors for treatment or tissue augmentation has come to the fore owing to advancements in computing power, modeling frameworks, and translational successes. Shorter proteins, or peptides, can offer combinatorial ...

Analyzing Antibody Repertoire Using Next-Generation Sequencing and Machine Learning.

Methods in molecular biology (Clifton, N.J.)
Advances in high-throughput sequencing technologies have enabled comprehensive sequencing of the immune repertoire. Since repertoire analysis can help to explain the relationship between the immune system and diseases, several methods have been devel...