AIMC Topic: Chromosome Mapping

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A machine learning enhanced EMS mutagenesis probability map for efficient identification of causal mutations in Caenorhabditis elegans.

PLoS genetics Aug 26, 2024
Chemical mutagenesis-driven forward genetic screens are pivotal in unveiling gene functions, yet identifying causal mutations behind phenotypes remains laborious, hindering their high-throughput application. Here, we reveal a non-uniform mutation rat...
Mutation Whole Genome Sequencing Mutagenesis Machine Learning Phenotype Animals Chromosome Mapping Kinesins Ethyl Methanesulfonate Mutation Rate Caenorhabditis elegans Caenorhabditis elegans Proteins
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GEMA: A Genome Exact Mapping Accelerator Based on Learned Indexes.

IEEE transactions on biomedical circuits and systems May 28, 2024
In this article, we introduce GEMA, a genome exact mapping accelerator based on learned indexes, specifically designed for FPGA implementation. GEMA utilizes a machine learning (ML) algorithm to precisely locate the exact position of read sequences w...
Humans Algorithms Machine Learning Sequence Analysis, DNA Chromosome Mapping
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Combining Digital and Molecular Approaches Using Health and Alternate Data Sources in a Next-Generation Surveillance System for Anticipating Outbreaks of Pandemic Potential.

JMIR public health and surveillance Jan 9, 2024
Globally, millions of lives are impacted every year by infectious diseases outbreaks. Comprehensive and innovative surveillance strategies aiming at early alert and timely containment of emerging and reemerging pathogens are a pressing priority. Shor...
Chromosome Mapping Disease Outbreaks Data Science Humans Influenza A Virus, H1N1 Subtype Artificial Intelligence
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Ten quick tips for sequence-based prediction of protein properties using machine learning.

PLoS computational biology Dec 1, 2022
The ubiquitous availability of genome sequencing data explains the popularity of machine learning-based methods for the prediction of protein properties from their amino acid sequences. Over the years, while revising our own work, reading submitted m...
Amino Acid Sequence Knowledge Chromosome Mapping Machine Learning
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DeepBSA: A deep-learning algorithm improves bulked segregant analysis for dissecting complex traits.

Molecular plant Aug 22, 2022
Bulked segregant analysis (BSA) is a rapid, cost-effective method for mapping mutations and quantitative trait loci (QTLs) in animals and plants based on high-throughput sequencing. However, the algorithms currently used for BSA have not been systema...
Animals Deep Learning Quantitative Trait Loci Algorithms Chromosome Mapping Multifactorial Inheritance
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Machine Learning Methods for Exploring Sequence Determinants of 3D Genome Organization.

Journal of molecular biology Jun 2, 2022
In higher eukaryotic cells, chromosomes are folded inside the nucleus. Recent advances in whole-genome mapping technologies have revealed the multiscale features of 3D genome organization that are intertwined with fundamental genome functions. Howeve...
Chromosome Mapping Chromatin Machine Learning Imaging, Three-Dimensional Sequence Analysis, DNA Cell Nucleus Genome Chromosomes
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Genetic dissection of complex traits using hierarchical biological knowledge.

PLoS computational biology Sep 17, 2021
Despite the growing constellation of genetic loci linked to common traits, these loci have yet to account for most heritable variation, and most act through poorly understood mechanisms. Recent machine learning (ML) systems have used hierarchical bio...
Glycine Knowledge Bases Saccharomyces cerevisiae Gene Ontology Hydroxyurea Neural Networks, Computer Chromosome Mapping Copper Mutation Models, Genetic Glucose Machine Learning Polymorphism, Single Nucleotide Metabolic Networks and Pathways Multifactorial Inheritance Computational Biology Phenotype Systems Biology Benomyl Genome-Wide Association Study Nucleotidyltransferases
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NanoCaller for accurate detection of SNPs and indels in difficult-to-map regions from long-read sequencing by haplotype-aware deep neural networks.

Genome biology Sep 6, 2021
Long-read sequencing enables variant detection in genomic regions that are considered difficult-to-map by short-read sequencing. To fully exploit the benefits of longer reads, here we present a deep learning method NanoCaller, which detects SNPs usin...
Chromosome Mapping Major Histocompatibility Complex Nanopore Sequencing Genome, Human INDEL Mutation Nanoparticles Benchmarking Humans Alleles Neural Networks, Computer Polymorphism, Single Nucleotide High-Throughput Nucleotide Sequencing Haplotypes Base Sequence
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Leveraging supervised learning for functionally informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLs.

Nature communications Jun 7, 2021
The large majority of variants identified by GWAS are non-coding, motivating detailed characterization of the function of non-coding variants. Experimental methods to assess variants' effect on gene expressions in native chromatin context via direct ...
Humans Adult Gene Expression Profiling Cohort Studies Polymorphism, Single Nucleotide Computational Biology Quantitative Trait Loci Supervised Machine Learning Chromosome Mapping Datasets as Topic
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CBCR: A Curriculum Based Strategy For Chromosome Reconstruction.

International journal of molecular sciences Apr 16, 2021
In this paper, we introduce a novel algorithm that aims to estimate chromosomes' structure from their Hi-C contact data, called Curriculum Based Chromosome Reconstruction (CBCR). Specifically, our method performs this three dimensional reconstruction...
Models, Genetic Chromosomes Humans Chromosome Mapping Machine Learning
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