AIMC Topic: Genome, Viral
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DeLUCS: Deep learning for unsupervised clustering of DNA sequences.
PloS one
Jan 21, 2022
We present a novel Deep Learning method for the Unsupervised Clustering of DNA Sequences (DeLUCS) that does not require sequence alignment, sequence homology, or (taxonomic) identifiers. DeLUCS uses Frequency Chaos Game Representations (FCGR) of prim...
Identification of the tail assembly chaperone genes of T4-Like phages suggests a mechanism other than translational frameshifting for biogenesis of their encoded proteins.
Virology
Nov 18, 2021
Tape measure (TM) proteins are essential for the formation of long-tailed phages. TM protein assembly into tails requires the action of tail assembly chaperones (TACs). TACs (e.g. gpG and gpT of E. coli phage lambda) are usually produced in a short (...
The viral expression and immune status in human cancers and insights into novel biomarkers of immunotherapy.
BMC cancer
Nov 5, 2021
BACKGROUND: Viral infections are prevalent in human cancers and they have great diagnostic and theranostic values in clinical practice. Recently, their potential of shaping the tumor immune microenvironment (TIME) has been related to the immunotherap...
Humans
Machine Learning
Stomach Neoplasms
Papillomaviridae
Oncogenic Viruses
High-Throughput Nucleotide Sequencing
Genome, Viral
Tumor Virus Infections
Kaplan-Meier Estimate
Head and Neck Neoplasms
Support Vector Machine
RNA-Seq
DNA, Viral
Tumor Microenvironment
Immunotherapy
Herpesvirus 4, Human
Epstein-Barr Virus Infections
Biomarkers, Tumor
Papillomavirus Infections
Mutation
Neoplasms
Squamous Cell Carcinoma of Head and Neck
Leukocytes
Transcriptome
Genetic Variation
AI for the collective analysis of a massive number of genome sequences: various examples from the small genome of pandemic SARS-CoV-2 to the human genome.
Genes & genetic systems
Sep 27, 2021
In genetics and related fields, huge amounts of data, such as genome sequences, are accumulating, and the use of artificial intelligence (AI) suitable for big data analysis has become increasingly important. Unsupervised AI that can reveal novel know...
Machine-learning a virus assembly fitness landscape.
PloS one
May 5, 2021
Realistic evolutionary fitness landscapes are notoriously difficult to construct. A recent cutting-edge model of virus assembly consists of a dodecahedral capsid with 12 corresponding packaging signals in three affinity bands. This whole genome/pheno...
Predicting the animal hosts of coronaviruses from compositional biases of spike protein and whole genome sequences through machine learning.
PLoS pathogens
Apr 20, 2021
The COVID-19 pandemic has demonstrated the serious potential for novel zoonotic coronaviruses to emerge and cause major outbreaks. The immediate animal origin of the causative virus, SARS-CoV-2, remains unknown, a notoriously challenging task for eme...
Utilizing Computational Machine Learning Tools to Understand Immunogenic Breadth in the Context of a CD8 T-Cell Mediated HIV Response.
Frontiers in immunology
Feb 18, 2021
Predictive models are becoming more and more commonplace as tools for candidate antigen discovery to meet the challenges of enabling epitope mapping of cohorts with diverse HLA properties. Here we build on the concept of using two key parameters, div...
A protocol for adding knowledge to Wikidata: aligning resources on human coronaviruses.
BMC biology
Jan 22, 2021
BACKGROUND: Pandemics, even more than other medical problems, require swift integration of knowledge. When caused by a new virus, understanding the underlying biology may help finding solutions. In a setting where there are a large number of loosely ...
A Novel Protein Mapping Method for Predicting the Protein Interactions in COVID-19 Disease by Deep Learning.
Interdisciplinary sciences, computational life sciences
Jan 12, 2021
The new type of corona virus (SARS-COV-2) emerging in Wuhan, China has spread rapidly to the world and has become a pandemic. In addition to having a significant impact on daily life, it also shows its effect in different areas, including public heal...
Sequence-to-function deep learning frameworks for engineered riboregulators.
Nature communications
Oct 7, 2020
While synthetic biology has revolutionized our approaches to medicine, agriculture, and energy, the design of completely novel biological circuit components beyond naturally-derived templates remains challenging due to poorly understood design rules....
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