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Full-Text Articles in Life Sciences
Biosimp: Using Software Testing Techniques For Sampling And Inference In Biological Organisms, Mikaela Cashman, Jennie L. Catlett, Myra B. Cohen, Nicole R. Buan, Zahmeeth Sakkaff, Massimiliano Pierobon, Christine A. Kelley
Biosimp: Using Software Testing Techniques For Sampling And Inference In Biological Organisms, Mikaela Cashman, Jennie L. Catlett, Myra B. Cohen, Nicole R. Buan, Zahmeeth Sakkaff, Massimiliano Pierobon, Christine A. Kelley
CSE Conference and Workshop Papers
Years of research in software engineering have given us novel ways to reason about, test, and predict the behavior of complex software systems that contain hundreds of thousands of lines of code. Many of these techniques have been inspired by nature such as genetic algorithms, swarm intelligence, and ant colony optimization. In this paper we reverse the direction and present BioSIMP, a process that models and predicts the behavior of biological organisms to aid in the emerging field of systems biology. It utilizes techniques from testing and modeling of highly-configurable software systems. Using both experimental and simulation data we show …
Mutations Of Adjacent Amino Acid Pairs Are Not Always Independent, Jyotsna Ramanan, Peter Revesz
Mutations Of Adjacent Amino Acid Pairs Are Not Always Independent, Jyotsna Ramanan, Peter Revesz
CSE Conference and Workshop Papers
Evolutionary studies usually assume that the genetic mutations are independent of each other. This paper tests the independence hypothesis for genetic mutations with regard to protein coding regions. According to the new experimental results the independence assumption generally holds, but there are certain exceptions. In particular, the coding regions that represent two adjacent amino acids seem to change in ways that sometimes deviate significantly from the expected theoretical probability under the independence assumption.
A Computational Model Of The Spread Of Ancient Human Populations Based On Mitochondrial Dna Samples, Peter Revesz
A Computational Model Of The Spread Of Ancient Human Populations Based On Mitochondrial Dna Samples, Peter Revesz
CSE Conference and Workshop Papers
The extraction of mitochondrial DNA (mtDNA) from ancient human population samples provides important data for the reconstruction of population influences, spread and evolution from the Neolithic to the present. This paper presents a mtDNA-based similarity measure between pairs of human populations and a computational model for the evolution of human populations. In a computational experiment, the paper studies the mtDNA information from five Neolithic and Bronze Age populations, namely the Andronovo, the Bell Beaker, the Minoan, the Rössen and the Únětice populations. In the past these populations were identified as separate cultural groups based on geographic location, age and the …
An Incremental Phylogenetic Tree Algorithm Based On Repeated Insertions Of Species, Peter Revesz, Zhiqiang Li
An Incremental Phylogenetic Tree Algorithm Based On Repeated Insertions Of Species, Peter Revesz, Zhiqiang Li
CSE Conference and Workshop Papers
In this paper, we introduce a new phylogenetic tree algorithm that generates phylogenetic trees by repeatedly inserting species one-by-one. The incremental phylogenetic tree algorithm can work on proteins or DNA sequences. Computer experiments show that the new algorithm is better than the commonly used UPGMA and Neighbor Joining algorithms.
Classification And Cluster Analysis Of Complex Time-Of-Flight Secondary Ion Mass Spectrometry For Biological Samples, Stephen E. Reichenbach, Xue Tian, Qingping Tao, Alex Henderson
Classification And Cluster Analysis Of Complex Time-Of-Flight Secondary Ion Mass Spectrometry For Biological Samples, Stephen E. Reichenbach, Xue Tian, Qingping Tao, Alex Henderson
CSE Conference and Workshop Papers
Identifying and separating subtly different biological samples is one of the most critical tasks in biological analysis. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is becoming a popular and important technique in the analysis of biological samples, because it can detect molecular information and characterize chemical composition. ToF-SIMS spectra of biological samples are enormously complex with large mass ranges and many peaks. As a result the classification and cluster analysis are challenging. This study presents a new classification algorithm, the most similar neighbor with a probability-based spectrum similarity measure (MSN- PSSM), which uses all the information in the entire ToF- SIMS …