AIMC Topic: Genome, Plant

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RiceSNP-BST: a deep learning framework for predicting biotic stress-associated SNPs in rice.

Briefings in bioinformatics Sep 23, 2024
Rice consistently faces significant threats from biotic stresses, such as fungi, bacteria, pests, and viruses. Consequently, accurately and rapidly identifying previously unknown single-nucleotide polymorphisms (SNPs) in the rice genome is a critical...
Software Oryza Stress, Physiological Genome, Plant Deep Learning Genome-Wide Association Study Polymorphism, Single Nucleotide
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PTFSpot: deep co-learning on transcription factors and their binding regions attains impeccable universality in plants.

Briefings in bioinformatics May 23, 2024
Unlike animals, variability in transcription factors (TFs) and their binding regions (TFBRs) across the plants species is a major problem that most of the existing TFBR finding software fail to tackle, rendering them hardly of any use. This limitatio...
Genome, Plant Arabidopsis Plants Binding Sites Deep Learning Computational Biology Transcription Factors Software
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SoyDNGP: a web-accessible deep learning framework for genomic prediction in soybean breeding.

Briefings in bioinformatics Sep 22, 2023
Soybean is a globally significant crop, playing a vital role in human nutrition and agriculture. Its complex genetic structure and wide trait variation, however, pose challenges for breeders and researchers aiming to optimize its yield and quality. A...
Genome, Plant Plant Breeding Deep Learning Genomics Humans Glycine max Phenotype
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miWords: transformer-based composite deep learning for highly accurate discovery of pre-miRNA regions across plant genomes.

Briefings in bioinformatics Mar 19, 2023
Discovering pre-microRNAs (miRNAs) is the core of miRNA discovery. Using traditional sequence/structural features, many tools have been published to discover miRNAs. However, in practical applications like genomic annotations, their actual performanc...
Software MicroRNAs Genome, Plant Arabidopsis Animals Deep Learning Genomics
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Inpactor2: a software based on deep learning to identify and classify LTR-retrotransposons in plant genomes.

Briefings in bioinformatics Jan 19, 2023
LTR-retrotransposons are the most abundant repeat sequences in plant genomes and play an important role in evolution and biodiversity. Their characterization is of great importance to understand their dynamics. However, the identification and classif...
Retroelements Terminal Repeat Sequences Evolution, Molecular Genome, Plant Software Phylogeny Deep Learning
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Meta-i6mA: an interspecies predictor for identifying DNA N6-methyladenine sites of plant genomes by exploiting informative features in an integrative machine-learning framework.

Briefings in bioinformatics May 20, 2021
DNA N6-methyladenine (6mA) represents important epigenetic modifications, which are responsible for various cellular processes. The accurate identification of 6mA sites is one of the challenging tasks in genome analysis, which leads to an understandi...
DNA, Plant Arabidopsis Rosaceae Species Specificity Adenosine Genome, Plant Oryza Base Sequence Algorithms Computational Biology Epigenesis, Genetic Models, Genetic Support Vector Machine Internet Machine Learning
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Prediction of Rice Transcription Start Sites Using TransPrise: A Novel Machine Learning Approach.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2021
As the interest in genetic resequencing increases, so does the need for effective mathematical, computational, and statistical approaches. One of the difficult problems in genome annotation is determination of precise positions of transcription start...
Machine Learning Software Oryza Plant Proteins Promoter Regions, Genetic Gene Expression Regulation, Plant Transcription Initiation Site Transcription, Genetic Genome, Plant
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Revisiting CRISPR/Cas-mediated crop improvement: Special focus on nutrition.

Journal of biosciences Jan 1, 2020
Genome editing (GE) technology has emerged as a multifaceted strategy that instantaneously popularised the mechanism to modify the genetic constitution of an organism. The clustered regularly interspaced short palindromic repeat (CRISPR) and CRISPR-a...
Genome, Plant Gene Editing DNA Breaks, Double-Stranded Endonucleases CRISPR-Cas Systems Crops, Agricultural Artificial Intelligence
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Computational aspects underlying genome to phenome analysis in plants.

The Plant journal : for cell and molecular biology Jan 1, 2019
Recent advances in genomics technologies have greatly accelerated the progress in both fundamental plant science and applied breeding research. Concurrently, high-throughput plant phenotyping is becoming widely adopted in the plant community, promisi...
Machine Learning Phenotype Genomics Quantitative Trait Loci Genetic Association Studies Phenomics Plants Genome, Plant
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Applications of Machine Learning Methods to Genomic Selection in Breeding Wheat for Rust Resistance.

The plant genome Jul 1, 2018
New methods and algorithms are being developed for predicting untested phenotypes in schemes commonly used in genomic selection (GS). The prediction of disease resistance in GS has its own peculiarities: a) there is consensus about the additive natur...
Genome, Plant Plant Breeding Genomics Models, Genetic Support Vector Machine Neural Networks, Computer Machine Learning Linear Models Basidiomycota Triticum Disease Resistance Plant Diseases
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