Genome-scale RNAi screens for high-throughput phenotyping in bloodstream-form African trypanosomes

2014 ◽  
Vol 10 (1) ◽  
pp. 106-133 ◽  
Author(s):  
Lucy Glover ◽  
Sam Alsford ◽  
Nicola Baker ◽  
Daniel J Turner ◽  
Alejandro Sanchez-Flores ◽  
...  
Keyword(s):  
High Throughput ◽  
Bloodstream Form ◽  
African Trypanosomes ◽  
High Throughput Phenotyping ◽  
Genome Scale

scholarly journals Genome-scale Reconstruction of Metabolic Network inBacillus subtilisBased on High-throughput Phenotyping and Gene Essentiality Data

2007 ◽  
Vol 282 (39) ◽  
pp. 28791-28799 ◽  
Author(s):  
You-Kwan Oh ◽  
Bernhard O. Palsson ◽  
Sung M. Park ◽  
Christophe H. Schilling ◽  
Radhakrishnan Mahadevan
Keyword(s):  
Metabolic Network ◽  
High Throughput ◽  
Gene Essentiality ◽  
High Throughput Phenotyping ◽  
Genome Scale

scholarly journals High-throughput decoding of drug targets and drug resistance mechanisms in African trypanosomes

Parasitology ◽  
2013 ◽  
Vol 141 (1) ◽  
pp. 77-82 ◽  
Author(s):  
DAVID HORN
Keyword(s):  
Drug Resistance ◽  
High Throughput ◽  
Drug Targets ◽  
Sequence Data ◽  
Resistance Mechanisms ◽  
New Drugs ◽  
Drug Uptake ◽  
Microbial Pathogens ◽  
African Trypanosomes ◽  
Genome Scale

SUMMARYThe availability of genome sequence data has facilitated the development of high-throughput genetic screening approaches in microbial pathogens. In the African trypanosome, Trypanosoma brucei, genome-scale RNA interference screens have proven particularly effective in this regard. These genetic screens allow for identification of the genes that contribute to a particular pathway or mechanisms of interest. The approach has been used to assess loss-of-fitness, revealing the genes and proteins required for parasite viability and growth. The outputs from these screens predict essential and dispensable genes and facilitate drug target prioritization efforts. The approach has also been used to assess resistance to anti-trypanosomal drugs, revealing the genes and proteins that facilitate drug uptake and action. These outputs also highlight likely mechanisms underlying clinically relevant drug resistance. I first review these findings in the context of what we know about current drugs. I then describe potential contributions that these high-throughput approaches could make to the development and implementation of new drugs.

Towards high-throughput phenotyping of complex patterned behaviors: Lessons from mouse self-grooming

2011 ◽  
Author(s):  
E. Kyzar ◽  
S. Gaikwad ◽  
M. Pham ◽  
J. Green ◽  
A. Roth ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Phenotyping

scholarly journals High-throughput phenotyping: breaking through the bottleneck in future crop breeding

2021 ◽  
Author(s):  
Peng Song ◽  
Jinglu Wang ◽  
Xinyu Guo ◽  
Wanneng Yang ◽  
Chunjiang Zhao
Keyword(s):  
High Throughput ◽  
Crop Breeding ◽  
High Throughput Phenotyping

scholarly journals High-Throughput Phenotyping Methods for Breeding Drought-Tolerant Crops

2021 ◽  
Vol 22 (15) ◽  
pp. 8266
Author(s):  
Minsu Kim ◽  
Chaewon Lee ◽  
Subin Hong ◽  
Song Lim Kim ◽  
Jeong-Ho Baek ◽  
...  
Keyword(s):  
Drought Stress ◽  
High Throughput ◽  
Large Scale ◽  
Crop Yields ◽  
Plant Traits ◽  
Rapid Development ◽  
Plant Responses ◽  
Phenotypic Data ◽  
Agricultural Technologies ◽  
High Throughput Phenotyping

Drought is a main factor limiting crop yields. Modern agricultural technologies such as irrigation systems, ground mulching, and rainwater storage can prevent drought, but these are only temporary solutions. Understanding the physiological, biochemical, and molecular reactions of plants to drought stress is therefore urgent. The recent rapid development of genomics tools has led to an increasing interest in phenomics, i.e., the study of phenotypic plant traits. Among phenomic strategies, high-throughput phenotyping (HTP) is attracting increasing attention as a way to address the bottlenecks of genomic and phenomic studies. HTP provides researchers a non-destructive and non-invasive method yet accurate in analyzing large-scale phenotypic data. This review describes plant responses to drought stress and introduces HTP methods that can detect changes in plant phenotypes in response to drought.

scholarly journals High-throughput phenotyping of two plant-size traits of Eucalyptus species using neural networks

2021 ◽  
Author(s):  
Marcus Vinicius Vieira Borges ◽  
Janielle de Oliveira Garcia ◽  
Tays Silva Batista ◽  
Alexsandra Nogueira Martins Silva ◽  
Fabio Henrique Rojo Baio ◽  
...  
Keyword(s):  
Neural Networks ◽  
High Throughput ◽  
Mean Squared Error ◽  
Vegetation Indices ◽  
Plant Size ◽  
Eucalyptus Species ◽  
Forest Inventories ◽  
Spectral Bands ◽  
High Throughput Phenotyping ◽  
Input Variables

AbstractIn forest modeling to estimate the volume of wood, artificial intelligence has been shown to be quite efficient, especially using artificial neural networks (ANNs). Here we tested whether diameter at breast height (DBH) and the total plant height (Ht) of eucalyptus can be predicted at the stand level using spectral bands measured by an unmanned aerial vehicle (UAV) multispectral sensor and vegetation indices. To do so, using the data obtained by the UAV as input variables, we tested different configurations (number of hidden layers and number of neurons in each layer) of ANNs for predicting DBH and Ht at stand level for different Eucalyptus species. The experimental design was randomized blocks with four replicates, with 20 trees in each experimental plot. The treatments comprised five Eucalyptus species (E. camaldulensis, E. uroplylla, E. saligna, E. grandis, and E. urograndis) and Corymbria citriodora. DBH and Ht for each plot at the stand level were measured seven times in separate overflights by the UAV, so that the multispectral sensor could obtain spectral bands to calculate vegetation indices (VIs). ANNs were then constructed using spectral bands and VIs as input layers, in addition to the categorical variable (species), to predict DBH and Ht at the stand level simultaneously. This report represents one of the first applications of high-throughput phenotyping for plant size traits in Eucalyptus species. In general, ANNs containing three hidden layers gave better statistical performance (higher estimated r, lower estimated root mean squared error–RMSE) due to their greater capacity for self-learning. Among these ANNs, the best contained eight neurons in the first layer, seven in the second, and five in the third (8 − 7 − 5). The results reported here reveal the potential of using the generated models to perform accurate forest inventories based on spectral bands and VIs obtained with a UAV multispectral sensor and ANNs, reducing labor and time.

scholarly journals High-throughput phenotyping (HTP) identifies seedling root traits linked to variation in seed yield and nutrient capture in field-grown oilseed rape (Brassica napusL.)

2016 ◽  
Vol 118 (4) ◽  
pp. 655-665 ◽  
Author(s):  
C. L. Thomas ◽  
N. S. Graham ◽  
R. Hayden ◽  
M. C. Meacham ◽  
K. Neugebauer ◽  
...  
Keyword(s):  
Oilseed Rape ◽  
Seed Yield ◽  
High Throughput ◽  
Root Traits ◽  
Seedling Root ◽  
High Throughput Phenotyping
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