Machine learning: its challenges and opportunities in plant system biology
Sequencing technologies are evolving at a rapid pace, enabling the generation of massive
amounts of data in multiple dimensions (eg, genomics, epigenomics, transcriptomic …
amounts of data in multiple dimensions (eg, genomics, epigenomics, transcriptomic …
DeepBIO: an automated and interpretable deep-learning platform for high-throughput biological sequence prediction, functional annotation and visualization analysis
Here, we present DeepBIO, the first-of-its-kind automated and interpretable deep-learning
platform for high-throughput biological sequence functional analysis. DeepBIO is a one-stop …
platform for high-throughput biological sequence functional analysis. DeepBIO is a one-stop …
iDNA-ABT: advanced deep learning model for detecting DNA methylation with adaptive features and transductive information maximization
Motivation DNA methylation plays an important role in epigenetic modification, the
occurrence, and the development of diseases. Therefore, identification of DNA methylation …
occurrence, and the development of diseases. Therefore, identification of DNA methylation …
scDeepSort: a pre-trained cell-type annotation method for single-cell transcriptomics using deep learning with a weighted graph neural network
Advances in single-cell RNA sequencing (scRNA-seq) have furthered the simultaneous
classification of thousands of cells in a single assay based on transcriptome profiling. In …
classification of thousands of cells in a single assay based on transcriptome profiling. In …
Meta-i6mA: an interspecies predictor for identifying DNA N6-methyladenine sites of plant genomes by exploiting informative features in an integrative machine …
Abstract DNA N 6-methyladenine (6mA) represents important epigenetic modifications,
which are responsible for various cellular processes. The accurate identification of 6mA sites …
which are responsible for various cellular processes. The accurate identification of 6mA sites …
Anticancer peptides prediction with deep representation learning features
Anticancer peptides constitute one of the most promising therapeutic agents for combating
common human cancers. Using wet experiments to verify whether a peptide displays …
common human cancers. Using wet experiments to verify whether a peptide displays …
DeepM6ASeq-EL: prediction of human N6-methyladenosine (m6A) sites with LSTM and ensemble learning
Abstract N6-methyladenosine (m 6 A) is a prevalent methylation modification and plays a
vital role in various biological processes, such as metabolism, mRNA processing, synthesis …
vital role in various biological processes, such as metabolism, mRNA processing, synthesis …
Computational prediction and interpretation of cell-specific replication origin sites from multiple eukaryotes by exploiting stacking framework
Origins of replication sites (ORIs), which refers to the initiative locations of genomic DNA
replication, play essential roles in DNA replication process. Detection of ORIs' distribution in …
replication, play essential roles in DNA replication process. Detection of ORIs' distribution in …
DeepYY1: a deep learning approach to identify YY1-mediated chromatin loops
Abstract The protein Yin Yang 1 (YY1) could form dimers that facilitate the interaction
between active enhancers and promoter-proximal elements. YY1-mediated enhancer …
between active enhancers and promoter-proximal elements. YY1-mediated enhancer …
[HTML][HTML] Multi-correntropy fusion based fuzzy system for predicting DNA N4-methylcytosine sites
The identification of DNA N4-methylcytosine (4mC) sites is an important field of
bioinformatics. Statistical learning methods and deep learning have been applied in this …
bioinformatics. Statistical learning methods and deep learning have been applied in this …