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Caenorhabditis elegans

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MiRNATIP: a SOM-based miRNA-target interactions predictor.

BMC bioinformatics
BACKGROUND: MicroRNAs (miRNAs) are small non-coding RNA sequences with regulatory functions to post-transcriptional level for several biological processes, such as cell disease progression and metastasis. MiRNAs interact with target messenger RNA (mR...

Computationally predicting protein-RNA interactions using only positive and unlabeled examples.

Journal of bioinformatics and computational biology
Protein-RNA interactions (PRIs) are considerably important in a wide variety of cellular processes, ranging from transcriptional and post-transcriptional regulations of gene expression to the active defense of host against virus. With the development...

Developmental time windows for axon growth influence neuronal network topology.

Biological cybernetics
Early brain connectivity development consists of multiple stages: birth of neurons, their migration and the subsequent growth of axons and dendrites. Each stage occurs within a certain period of time depending on types of neurons and cortical layers....

Deep learning-based enhancement of fluorescence labeling for accurate cell lineage tracing during embryogenesis.

Bioinformatics (Oxford, England)
MOTIVATION: Automated cell lineage tracing throughout embryogenesis plays a key role in the study of regulatory control of cell fate differentiation, morphogenesis and organogenesis in the development of animals, including nematode Caenorhabditis ele...

Expression and Purification of SMGL-1.

Studies in health technology and informatics
Recombinant protein expression is a crucial technique in biology, with E. coli being the most widely used expression system. However, due to growth pressure, the expression of large molecular weight proteins in E. coli has remained a challenging task...

Scan-less machine-learning-enabled incoherent microscopy for minimally-invasive deep-brain imaging.

Optics express
Deep-brain microscopy is strongly limited by the size of the imaging probe, both in terms of achievable resolution and potential trauma due to surgery. Here, we show that a segment of an ultra-thin multi-mode fiber (cannula) can replace the bulky mic...

Dynamic Markers for Chaotic Motion in C. elegans.

Nonlinear dynamics, psychology, and life sciences
We describe the locomotion of Caenorhabditis elegans (C. elegans) using nonlinear dynamics. C. elegans is a commonly studied model organism based on ease of maintenance and simple neurological structure. In contrast to traditional microscopic techniq...

Machine learning approach to gene essentiality prediction: a review.

Briefings in bioinformatics
UNLABELLED: Essential genes are critical for the growth and survival of any organism. The machine learning approach complements the experimental methods to minimize the resources required for essentiality assays. Previous studies revealed the need to...

Organizing principles of the C. elegans contactome.

Cell systems
Two recent studies published in Nature generate and analyze, for the first time, the network of ∼100,000 membrane contacts between neurons in the C. elegans nerve ring. These novel data, extracted from legacy electron microscographs, represent a shif...

Toward a living soft microrobot through optogenetic locomotion control of .

Science robotics
Learning from the locomotion of natural organisms is one of the most effective strategies for designing microrobots. However, the development of bioinspired microrobots is still challenging because of technical bottlenecks such as design and seamless...