Machine Learning Predictions Electronic Couplings for Charge Transport Calculations of P3HT

The purpose of this work is to lower the computational cost of predicting charge mobilities in organic semiconductors, which will benefit the screening of candidates for inexpensive solar power generation. We characterize efforts to minimize the number of expensive quantum chemical calculations we perform by training machines to predict electronic couplings between monomers of poly-(3-hexylthiophene). We test five machine learning techniques and identify random forests as the most accurate, information-dense, and easy-to-implement approach for this problem, achieving mean-absolute-error of 0.02 [× 1.6 × 10−19 J], R2 = 0.986, predicting electronic couplings 390 times faster than quantum chemical calculations, and informing zero-field hole mobilities within 5% of prior work. We discuss strategies for identifying small effective training sets. In sum, we demonstrate an example problem where machine learning techniques provide an effective reduction in computational costs while helping to understand underlying structure–property relationships in a materials system with broad applicability

Hundreds of microsatellites for genotyping Plasmodium yoelii parasites

Genetic crosses have been employed to study various traits of rodent malaria parasites and to locate loci that contribute to drug resistance, immune protection, and disease virulence. Compared with human malaria parasites, genetic crossing of rodent malaria parasites is more easily performed; however, genotyping methods using microsatellites (MSs) or large-scale single nucleotide polymorphisms (SNPs) that have been widely used in typing Plasmodium falciparum are not available for rodent malaria species. Here we report a genome-wide search of the Plasmodium yoelii yoelii (P. yoelii) genome for simple sequence repeats (SSRs) and the identification of nearly 600 polymorphic MS markers for typing the genomes of P, yoelii and Plasmodium berghei. The MS markers are randomly distributed across the 14 physical chromosomes assembled from genome sequences of three rodent malaria species, although some variations in the numbers of MS expected according to chromosome size exist. The majority of the MS markers are AT-rich repeats, similar to those found in the P. falciparum genome. The MS markers provide an important resource for genotyping, lay a foundation for developing linkage maps, and will greatly facilitate genetic studies of P. yoelii. Published by Elsevier B.V

Linkage maps from multiple genetic crosses and loci linked to growth-related virulent phenotype in Plasmodium yoelii

Plasmodium yoelii is an excellent model for studying malaria pathogenesis that is often intractable to investigate using human parasites; however, genetic studies of the parasite have been hindered by lack of genome-wide linkage resources. Here, we performed 14 genetic crosses between three pairs of P. yoelii clones/subspecies, isolated 75 independent recombinant progeny from the crosses, and constructed a high-resolution linkage map for this parasite. Microsatellite genotypes from the progeny formed 14 linkage groups belonging to the 14 parasite chromosomes, allowing assignment of sequence contigs to chromosomes. Growth-related virulent phenotypes from 25 progeny of one of the crosses were significantly associated with a major locus on chromosome 13 and with two secondary loci on chromosomes 7 and 10. The chromosome 10 and 13 loci are both linked to day 5 parasitemia, and their effects on parasite growth rate are independent but additive. The locus on chromosome 7 is associated with day 10 parasitemia. The chromosome 13 locus spans similar to 220 kb of DNA containing 51 predicted genes, including the P. yoelii erythrocyte binding ligand, in which a C741Y substitution in the R6 domain is implicated in the change of growth rate. Similarly, the chromosome 10 locus spans similar to 234 kb with 71 candidate genes, containing a member of the 235-kDa rhoptry proteins (Py235) that can bind to the erythrocyte surface membrane. Atypical virulent phenotypes among the progeny were also observed. This study provides critical tools and information for genetic investigations of virulence and biology of P. yoelii.National Basic Research Program of China, 973 Program[2007CB513103]; Science Planning Program of Fujian Province[2010J1008]; 111 Project of Education of China[B06016]; Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health; National Center for Biotechnology Information, National Library of Medicine, National Institutes of Healt