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The Genome3D Consortium for Structural Annotations of Selected Model Organisms.

Methods in molecular biology (Clifton, N.J.)
Genome3D consortium is a collaborative project involving protein structure prediction and annotation resources developed by six world-leading structural bioinformatics groups, based in the United Kingdom (namely Blundell, Murzin, Gough, Sternberg, Or...

Ab initio GO-based mining for non-tandem-duplicated functional clusters in three model plant diploid genomes.

PloS one
A functional Non-Tandem Duplicated Cluster (FNTDC) is a group of non-tandem-duplicated genes that are located closer than expected by mere chance and have a role in the same biological function. The identification of secondary-compounds-related FNTDC...

Quantification of Mechanical Forces and Physiological Processes Involved in Pollen Tube Growth Using Microfluidics and Microrobotics.

Methods in molecular biology (Clifton, N.J.)
Pollen tubes face many obstacles on their way to the ovule. They have to decide whether to navigate around cells or penetrate the cell wall and grow through it or even within it. Besides chemical sensing, which directs the pollen tubes on their path ...

SemanticGO: a tool for gene functional similarity analysis in Arabidopsis thaliana and rice.

Plant science : an international journal of experimental plant biology
Gene or pathway functional similarities are important information for researchers. However, these similarities are often described sparsely and qualitatively. The latent semantic analysis of Arabidopsis thaliana (Arabidopsis) Gene Ontology (GO) data ...

Multi-feature fusion for deep learning to predict plant lncRNA-protein interaction.

Genomics
Long non-coding RNAs (lncRNAs) play key roles in regulating cellular biological processes through diverse molecular mechanisms including binding to RNA binding proteins. The majority of plant lncRNAs are functionally uncharacterized, thus, accurate p...

Prediction of condition-specific regulatory genes using machine learning.

Nucleic acids research
Recent advances in genomic technologies have generated data on large-scale protein-DNA interactions and open chromatin regions for many eukaryotic species. How to identify condition-specific functions of transcription factors using these data has bec...

EDeepSSP: Explainable deep neural networks for exact splice sites prediction.

Journal of bioinformatics and computational biology
Splice site prediction is crucial for understanding underlying gene regulation, gene function for better genome annotation. Many computational methods exist for recognizing the splice sites. Although most of the methods achieve a competent performanc...

Accurate prediction of DNA N-methylcytosine sites via boost-learning various types of sequence features.

BMC genomics
BACKGROUND: DNA N4-methylcytosine (4mC) is a critical epigenetic modification and has various roles in the restriction-modification system. Due to the high cost of experimental laboratory detection, computational methods using sequence characteristic...

m6A-Atlas: a comprehensive knowledgebase for unraveling the N6-methyladenosine (m6A) epitranscriptome.

Nucleic acids research
N 6-Methyladenosine (m6A) is the most prevalent RNA modification on mRNAs and lncRNAs. It plays a pivotal role during various biological processes and disease pathogenesis. We present here a comprehensive knowledgebase, m6A-Atlas, for unraveling the ...

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
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...