a-high-throughput-assay-for-prediction-chemical-toxicity-automated

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of <em>Caenorhabditis elegans</em>

Applying toxicity testing of chemicals in higher order organisms, such as mice or rats, is time-consuming and expensive, due to their long lifespan and ...

Qilu University of Technology(Shandong Academy of Sciences), China

Traditional toxicological studies have relied heavily on various animal models to understand the effect of various compounds in a biological context. Considering the great cost, complexity and time involved in experiments using higher order organisms. Researchers have been exploring alternative models that avoid these disadvantages. One example of such a model is the nematode Caenorhabditis elegans. There are some advantages of C. elegans, such as small size, short life cycle, well defined genome, ease of maintenance and efficient reproduction.

Classification and prediction of toxicity of chemicals using an automated phenotypic profiling of Caenorhabditis elegans.

Sequence similarity analysis is a basic method in computational biological studies. Determining the similarity of biological sequences is a vital step in much research, such as exploring the evolutionary relationship among species, gene function analysis, protein structure prediction, and sequence retrieving. This paper introduces a method that uses the theory of the gray-level co-occurrence matrix, which is important in image texture analysis, to define and calculate the features of a DNA sequence. The proposed method can make a quantitative analysis and compute the defined texture features of a DNA sequence. Using these quantified sequence features, a similarity distance matrix can be computed and phylogenetic relationships also can be inferred. From the quantified features, we found that the DNA sequence of humans has the highest entropy and lowest energy. From human to chimpanzee, orangutan, gorilla, and other species, the entropy decreases and energy increases. The advantage of the proposed method is that it can compute multiple features inherent in each sequence. Furthermore, the defined features can be the key values or tags for each sequence for sequence retrieval and similarity analysis.

Weiyang Chen

College of Computer Science and Technology

Qilu University of Technology(Shandong Academy of Sciences), China

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans

Weiyang Chen

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}College of Computer Science and Technology

Qilu University of Technology(Shandong Academy of Sciences), China

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans

College of Computer Science and Technology