AIMC Topic: Animals

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Uncovering the mouse olfactory long non-coding transcriptome with a novel machine-learning model.

DNA research : an international journal for rapid publication of reports on genes and genomes
Very little is known about long non-coding RNAs (lncRNAs) in the mammalian olfactory sensory epithelia. Deciphering the non-coding transcriptome in olfaction is relevant because these RNAs have been shown to play a role in chromatin modification and ...

DeepIsoFun: a deep domain adaptation approach to predict isoform functions.

Bioinformatics (Oxford, England)
MOTIVATION: Isoforms are mRNAs produced from the same gene locus by alternative splicing and may have different functions. Although gene functions have been studied extensively, little is known about the specific functions of isoforms. Recently, some...

Fast honey classification using infrared spectrum and machine learning.

Mathematical biosciences and engineering : MBE
Honey has been one previous natural food in human history. However, as the supply cannot satisfy the market demand, many incidents of adulterated and fraudulent honey have been reported. In Taiwan, some common adulterated honey and fraudulent honey i...

Accurate prediction of boundaries of high resolution topologically associated domains (TADs) in fruit flies using deep learning.

Nucleic acids research
Genomes are organized into self-interacting chromatin regions called topologically associated domains (TADs). A significant number of TAD boundaries are shared across multiple cell types and conserved across species. Disruption of TAD boundaries may ...

Multi-omics integration-a comparison of unsupervised clustering methodologies.

Briefings in bioinformatics
With the recent developments in the field of multi-omics integration, the interest in factors such as data preprocessing, choice of the integration method and the number of different omics considered had increased. In this work, the impact of these f...

DeeReCT-PolyA: a robust and generic deep learning method for PAS identification.

Bioinformatics (Oxford, England)
MOTIVATION: Polyadenylation is a critical step for gene expression regulation during the maturation of mRNA. An accurate and robust method for poly(A) signals (PASs) identification is not only desired for the purpose of better transcripts' end annota...

Context matters: using reinforcement learning to develop human-readable, state-dependent outbreak response policies.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
The number of all possible epidemics of a given infectious disease that could occur on a given landscape is large for systems of real-world complexity. Furthermore, there is no guarantee that the control actions that are optimal, on average, over all...

DeepMRMP: A new predictor for multiple types of RNA modification sites using deep learning.

Mathematical biosciences and engineering : MBE
RNA modification plays an indispensable role in the regulation of organisms. RNA modification site prediction offers an insight into diverse cellular processing. Regarding different types of RNA modification site prediction, it is difficult to tell t...