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Saccharomyces cerevisiae

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Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning.

Nature methods
In mass-spectrometry-based proteomics, the identification and quantification of peptides and proteins heavily rely on sequence database searching or spectral library matching. The lack of accurate predictive models for fragment ion intensities impair...

Identification of D Modification Sites by Integrating Heterogeneous Features in .

Molecules (Basel, Switzerland)
As an abundant post-transcriptional modification, dihydrouridine (D) has been found in transfer RNA (tRNA) from bacteria, eukaryotes, and archaea. Nonetheless, knowledge of the exact biochemical roles of dihydrouridine in mediating tRNA function is s...

Application of deep convolutional neural networks in classification of protein subcellular localization with microscopy images.

Genetic epidemiology
Single-cell microscopy image analysis has proved invaluable in protein subcellular localization for inferring gene/protein function. Fluorescent-tagged proteins across cellular compartments are tracked and imaged in response to genetic or environment...

Physicochemical property based computational scheme for classifying DNA sequence elements of Saccharomyces cerevisiae.

Computational biology and chemistry
GenerationE of huge "omics" data necessitates the development and application of computational methods to annotate the data in terms of biological features. In the context of DNA sequence, it is important to unravel the hidden physicochemical signatu...

Prediction of protein self-interactions using stacked long short-term memory from protein sequences information.

BMC systems biology
BACKGROUND: Self-interacting Proteins (SIPs) plays a critical role in a series of life function in most living cells. Researches on SIPs are important part of molecular biology. Although numerous SIPs data be provided, traditional experimental method...

Deep learning architectures for prediction of nucleosome positioning from sequences data.

BMC bioinformatics
BACKGROUND: Nucleosomes are DNA-histone complex, each wrapping about 150 pairs of double-stranded DNA. Their function is fundamental for one of the primary functions of Chromatin i.e. packing the DNA into the nucleus of the Eukaryote cells. Several b...

Protein function prediction from protein-protein interaction network using gene ontology based neighborhood analysis and physico-chemical features.

Journal of bioinformatics and computational biology
Protein Function Prediction from Protein-Protein Interaction Network (PPIN) and physico-chemical features using the Gene Ontology (GO) classification are indeed very useful for assigning biological or biochemical functions to a protein. They also lea...

Novel symmetry-based gene-gene dissimilarity measures utilizing Gene Ontology: Application in gene clustering.

Gene
In recent years DNA microarray technology, leading to the generation of high-volume biological data, has gained significant attention. To analyze this high volume gene-expression data, one such powerful tool is Clustering. For any clustering algorith...

MAPLE (modular automated platform for large-scale experiments), a robot for integrated organism-handling and phenotyping.

eLife
Lab organisms are valuable in part because of large-scale experiments like screens, but performing such experiments over long time periods by hand is arduous and error-prone. Organism-handling robots could revolutionize large-scale experiments in the...

NMFGO: Gene Function Prediction via Nonnegative Matrix Factorization with Gene Ontology.

IEEE/ACM transactions on computational biology and bioinformatics
Gene Ontology (GO) is a controlled vocabulary of terms that describe molecule function, biological roles, and cellular locations of gene products (i.e., proteins and RNAs), it hierarchically organizes more than 43,000 GO terms via the direct acyclic ...