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Caenorhabditis elegans

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Tissue enrichment analysis for C. elegans genomics.

BMC bioinformatics
BACKGROUND: Over the last ten years, there has been explosive development in methods for measuring gene expression. These methods can identify thousands of genes altered between conditions, but understanding these datasets and forming hypotheses base...

Supervised Learning for Detection of Duplicates in Genomic Sequence Databases.

PloS one
MOTIVATION: First identified as an issue in 1996, duplication in biological databases introduces redundancy and even leads to inconsistency when contradictory information appears. The amount of data makes purely manual de-duplication impractical, and...

A Model for Improving the Learning Curves of Artificial Neural Networks.

PloS one
In this article, the performance of a hybrid artificial neural network (i.e. scale-free and small-world) was analyzed and its learning curve compared to three other topologies: random, scale-free and small-world, as well as to the chemotaxis neural n...

CD-Based Indices for Link Prediction in Complex Network.

PloS one
Lots of similarity-based algorithms have been designed to deal with the problem of link prediction in the past decade. In order to improve prediction accuracy, a novel cosine similarity index CD based on distance between nodes and cosine value betwee...

Computer-Assisted Transgenesis of Caenorhabditis elegans for Deep Phenotyping.

Genetics
A major goal in the study of human diseases is to assign functions to genes or genetic variants. The model organism Caenorhabditis elegans provides a powerful tool because homologs of many human genes are identifiable, and large collections of geneti...

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...