AIMC Topic: Phenotype

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Improving prediction of phenotypic drug response on cancer cell lines using deep convolutional network.

BMC bioinformatics
BACKGROUND: Understanding the phenotypic drug response on cancer cell lines plays a vital role in anti-cancer drug discovery and re-purposing. The Genomics of Drug Sensitivity in Cancer (GDSC) database provides open data for researchers in phenotypic...

Recovering Wind-Induced Plant Motion in Dense Field Environments via Deep Learning and Multiple Object Tracking.

Plant physiology
Understanding the relationships between local environmental conditions and plant structure and function is critical for both fundamental science and for improving the performance of crops in field settings. Wind-induced plant motion is important in m...

Opportunities and Challenges in Phenotypic Screening for Neurodegenerative Disease Research.

Journal of medicinal chemistry
Toxic misfolded proteins potentially underly many neurodegenerative diseases, but individual targets which regulate these proteins and their downstream detrimental effects are often unknown. Phenotypic screening is an unbiased method to screen for no...

Design of a tomato classifier based on machine vision.

PloS one
This paper attempts to design an automated, efficient and intelligent tomato grading method that facilitates the graded selling of the fruit. Based on machine vision, the color images of tomatoes with different morphologies were studied, and the colo...

PhenPath: a tool for characterizing biological functions underlying different phenotypes.

BMC genomics
BACKGROUND: Many diseases are associated with complex patterns of symptoms and phenotypic manifestations. Parsimonious explanations aim at reconciling the multiplicity of phenotypic traits with the perturbation of one or few biological functions. For...

Phenotype annotation with the ontology of microbial phenotypes (OMP).

Journal of biomedical semantics
BACKGROUND: Microbial genetics has formed a foundation for understanding many aspects of biology. Systematic annotation that supports computational data mining should reveal further insights for microbes, microbiomes, and conserved functions beyond m...

Machine and deep learning meet genome-scale metabolic modeling.

PLoS computational biology
Omic data analysis is steadily growing as a driver of basic and applied molecular biology research. Core to the interpretation of complex and heterogeneous biological phenotypes are computational approaches in the fields of statistics and machine lea...

AMC-Net: Asymmetric and multi-scale convolutional neural network for multi-label HPA classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: The multi-label Human Protein Atlas (HPA) classification can yield a better understanding of human diseases and help doctors to enhance the automatic analysis of biomedical images. The existing automatic protein recognition...

Exploring the druggable space around the Fanconi anemia pathway using machine learning and mechanistic models.

BMC bioinformatics
BACKGROUND: In spite of the abundance of genomic data, predictive models that describe phenotypes as a function of gene expression or mutations are difficult to obtain because they are affected by the curse of dimensionality, given the disbalance bet...