All Stories

  1. Decoding RNA N 6-Methyladenosine Methylome of Wheat Using Machine Learning and Nanopore Direct RNA Sequencing
  2. deepTFBS: Improving within‐ and Cross‐Species Prediction of Transcription Factor Binding Using Deep Multi‐Task and Transfer Learning
  3. The N6-methyladenosine reader ECT1 regulates seed germination via gibberellic acid- and phytochrome B-mediated signaling
  4. Editorial: Applications of artificial intelligence, machine learning, and deep learning in plant breeding
  5. PEA-m6A: an ensemble learning framework for accurately predicting N6-methyladenosine modifications in plants
  6. Genome assembly of KA105, a new resource for maize molecular breeding and genomic research
  7. IPOP: An Integrative Plant Multi-omics Platform for Cross-species Comparison and Evolutionary Study
  8. Changes in m6A RNA methylation are associated with male sterility in wolfberry
  9. Global hypermethylation of the N6-methyladenosine RNA modification associated with apple heterografting
  10. G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction
  11. Time-resolved multiomics analysis of the genetic regulation of maize kernel moisture
  12. easyMF: A Web Platform for Matrix Factorization-Based Gene Discovery from Large-scale Transcriptome Data
  13. Genome optimization via virtual simulation to accelerate maize hybrid breeding
  14. SMART v1.0: A Database for Small Molecules with Functional Implications in Plants
  15. Evolutionary Implications of the RNA N6-Methyladenosine Methylome in Plants
  16. LightGBM: accelerated genomically designed crop breeding through ensemble learning
  17. Interactive Web-Based Annotation of Plant MicroRNAs with iwa-miRNA
  18. The genetic mechanism of heterosis utilization in maize improvement
  19. Editorial: Genomics-Enabled Crop Genetics
  20. easyMF: A Web Platform for Matrix Factorization-based Biological Discovery from Large-scale Transcriptome Data
  21. Interactive Web-based Annotation of Plant MicroRNAs with iwa-miRNA
  22. deepEA: a containerized web server for interactive analysis of epitranscriptome sequencing data
  23. Exploring transcriptional switches from pairwise, temporal and population RNA-Seq data using deepTS
  24. Author Correction: Integration of metabolome and transcriptome reveals flavonoid accumulation in the intergeneric hybrid between Brassica rapa and Raphanus sativus
  25. Integration of metabolome and transcriptome reveals flavonoid accumulation in the intergeneric hybrid between Brassica rapa and Raphanus sativus
  26. Evolution of the RNA N6-Methyladenosine Methylome Mediated by Genomic Duplication
  27. Hybrid sequencing reveals insight into heat sensing and signaling of bread wheat
  28. CAFU: a Galaxy framework for exploring unmapped RNA-Seq data
  29. Large expert-curated database for benchmarking document
  30. miRLocator: A Python Implementation and Web Server for Predicting miRNAs from Pre-miRNA Sequences
  31. Corrigendum: Transcriptome-Wide Annotation of m5C RNA Modifications Using Machine Learning
  32. Opaque-2 Regulates a Complex Gene Network Associated with Cell Differentiation and Storage Functions of Maize Endosperm
  33. A deep convolutional neural network approach for predicting phenotypes from genotypes
  34. PEA: an integrated R toolkit for plant epitranscriptome analysis
  35. Transcriptome-Wide Annotation of m5C RNA Modifications Using Machine Learning
  36. Evolutionary Origin, Gradual Accumulation and Functional Divergence of Heat Shock Factor Gene Family with Plant Evolution
  37. DeepGS: Predicting phenotypes from genotypes using Deep Learning
  38. PEA: an integrated R toolkit for plant epitranscriptome analysis
  39. Evolution of intron-poor clades and expression patterns of the glycosyltransferase family 47
  40. A systems approach to a spatio-temporal understanding of the drought stress response in maize
  41. Massive expansion and differential evolution of small heat shock proteins with wheat (Triticum aestivum L.) polyploidization
  42. An Effective Strategy for Trait Combinations in Multiple-Trait Genomic Selection
  43. A Meta-Analysis Based Method for Prioritizing Candidate Genes Involved in a Pre-specific Function
  44. Transcriptome Dynamics during Maize Endosperm Development
  45. Coexpression Network Analysis of Benign and Malignant Phenotypes of SIV-Infected Sooty Mangabey and Rhesus Macaque
  46. Application of Machine Learning-Based Classification to Genomic Selection and Performance Improvement
  47. miRLocator: Machine Learning-Based Prediction of Mature MicroRNAs within Plant Pre-miRNA Sequences
  48. A Census of Nuclear Cyanobacterial Recruits in the Plant Kingdom
  49. RNA Sequencing of Laser-Capture Microdissected Compartments of the Maize Kernel Identifies Regulatory Modules Associated with Endosperm Cell Differentiation
  50. DNA sequence and structure properties analysis reveals similarities and differences to promoters of stress responsive genes in Arabidopsis thaliana
  51. Machine learning for Big Data analytics in plants
  52. Relative importance of various regeneration mechanisms in different restoration stages of Quercus variabilis forest after selective logging
  53. Dynamic parent-of-origin effects on small interfering RNA expression in the developing maize endosperm
  54. Machine Learning–Based Differential Network Analysis: A Study of Stress-Responsive Transcriptomes in Arabidopsis
  55. Effects of drought stress on growth, physiological and biochemical parameters in fine roots of Quercus variabilis Bl. seedlings
  56. Fine root architecture, morphology, and biomass response to cutting in a Chinese cork oak (Quercus variabilis Blume) forest
  57. A novel two-layer SVM model in miRNA Drosha processing site detection
  58. Dynamic Expression of Imprinted Genes Associates with Maternally Controlled Nutrient Allocation during Maize Endosperm Development
  59. Changes in morphological, physiological, and biochemical responses to different levels of drought stress in chinese cork oak (Quercus variabilis Bl.) seedlings
  60. Using Amino Acid Factor Scores to Predict Avian-to-Human Transmission of Avian Influenza Viruses: A Machine Learning Study
  61. Effects of stump diameter, stump height, and cutting season onQuercus variabilisstump sprouting
  62. Predicting transmission of avian influenza A viruses from avian to human by using informative physicochemical properties
  63. The Reference Genome of the Halophytic Plant Eutrema salsugineum
  64. Effect of aboveground intervention on fine root mass, production, and turnover rate in a Chinese cork oak (Quercus variabilis Blume) forest
  65. KGBassembler: a karyotype-based genome assembler for Brassicaceae species
  66. Recognizing drosha processing sites by a two-step prediction model with structure and sequence information
  67. Application of the Gini Correlation Coefficient to Infer Regulatory Relationships in Transcriptome Analysis
  68. GPS-MBA: Computational Analysis of MHC Class II Epitopes in Type 1 Diabetes
  69. Accurately Predicting Transcription Start Sites Using Logitlinear Model and Local Oligonucleotide Frequencies
  70. Sequence similarity analysis of non-self CTL epitopes and mouse proteins using sequence alignment
  71. Inequalities and Duality in Gene Coexpression Networks of HIV-1 Infection Revealed by the Combination of the Double-Connectivity Approach and the Gini's Method
  72. Identification of true EST alignments for recognising transcribed regions
  73. Accurate Prediction of Alternatively Spliced Cassette Exons Using Evolutionary Conservation Information and Logitlinear Model
  74. Position-specific residue preference features around the ends of helices and strands and a novel strategy for the prediction of secondary structures
  75. Feature Mining and Integration for Improving the Prediction Accuracy of Translation Initiation Sites in Eukaryotic mRNAs