Identification of multidimensional Boolean patterns in microbial communities.

Background: Identification of complex multidimensional interaction patterns within microbial communities is the key to understand, modulate, and design beneficial microbiomes. Every community has members that fulfill an essential function affecting multiple other community members through secondary metabolism. Since microbial community members are often simultaneously involved in multiple relations, not all interaction patterns for such microorganisms are expected to exhibit a visually uninterrupted pattern.

The ability of human nuclear DNA to cause false positive low-abundance heteroplasmy calls varies across the mitochondrial genome.

Background: Low-abundance mutations in mitochondrial populations (mutations with minor allele frequency ≤ 1%), are associated with cancer, aging, and neurodegenerative disorders. While recent progress in high-throughput sequencing technology has significantly improved the heteroplasmy identification process, the ability of this technology to detect low-abundance mutations can be affected by the presence of similar sequences originating from nuclear DNA (nDNA). To determine to what extent nDNA can cause false positive low-abundance heteroplasmy calls, we have identified mitochondrial locations of all subsequences that are common or similar (one mismatch allowed) between nDNA and mitochondrial DNA (mtDNA).

Secondary Analysis of the NCI-60 Whole Exome Sequencing Data Indicates Significant Presence of Propionibacterium acnes Genomic Material in Leukemia (RPMI-8226) and Central Nervous System (SF-295, SF-539, and SNB-19) Cell Lines.

The NCI-60 human tumor cell line panel has been used in a broad range of cancer research over the last two decades. A landmark 2013 whole exome sequencing study of this panel added an exceptional new resource for cancer biologists. The complementary analysis of the sequencing data produced by this study suggests the presence of Propionibacterium acnes genomic sequences in almost half of the datasets, with the highest abundance in the leukemia (RPMI-8226) and central nervous system (SF-295, SF-539, and SNB-19) cell lines.

Probability distribution of power fluctuations in turbulence.

We study local power fluctuations in numerical simulations of stationary, homogeneous, isotropic turbulence in two and three dimensions with Gaussian forcing. Due to the near-Gaussianity of the one-point velocity distribution, the probability distribution function (pdf) of the local power is well modeled by the pdf of the product of two joint normally distributed variables. In appropriate units, this distribution is parametrized only by the mean dissipation rate, epsilon.

A priori study of subgrid-scale flux of a passive scalar in isotropic homogeneous turbulence.

We perform a direct numerical simulation (DNS) of forced homogeneous isotropic turbulence with a passive scalar that is forced by mean gradient. The DNS data are used to study the properties of subgrid-scale flux of a passive scalar in the framework of large eddy simulation (LES), such as alignment trends between the flux, resolved, and subgrid-scale flow structures. It is shown that the direction of the flux is strongly coupled with the subgrid-scale stress axes rather than the resolved flow quantities such as strain, vorticity, or scalar gradient.

Effect of the mutation rate and background size on the quality of pathogen identification.

Motivation: Genomic-based methods have significant potential for fast and accurate identification of organisms or even genes of interest in complex environmental samples (air, water, soil, food, etc.), especially when isolation of the target organism cannot be performed by a variety of reasons. Despite this potential, the presence of the unknown, variable and usually large quantities of background DNA can cause interference resulting in false positive outcomes.

Using Mutual Information to Discover Temporal Patterns in Gene Expression Data.

Finding relations among gene expressions involves the definition of the similarity between experimental data. A simplest similarity measure is the Correlation Coefficient. It is able to identify linear dependences only; moreover, is sensitive to experimental errors.

Human-blind probes and primers for dengue virus identification.

Reliable detection and identification of pathogens in complex biological samples, in the presence of contaminating DNA from a variety of sources, is an important and challenging diagnostic problem for the development of field tests. The problem is compounded by the difficulty of finding a single, unique genomic sequence that is present simultaneously in all genomes of a species of closely related pathogens and absent in the genomes of the host or the organisms that contribute to the sample background. Here we describe 'host-blind probe design'- a novel strategy of designing probes based on highly frequent genomic signatures found in the pathogen genomes of interest but absent from the host genome.