Aerial imagery dataset of lost oil wells.

Orphaned wells are wells for which the operator is unknown or insolvent. The location of hundreds of thousands of these wells remain unknown in the United States alone. Cost-effective techniques are essential to locate orphaned wells to address environmental problems.

Latent Dirichlet Allocation modeling of environmental microbiomes.

Interactions between stressed organisms and their microbiome environments may provide new routes for understanding and controlling biological systems. However, microbiomes are a form of high-dimensional data, with thousands of taxa present in any given sample, which makes untangling the interaction between an organism and its microbial environment a challenge. Here we apply Latent Dirichlet Allocation (LDA), a technique for language modeling, which decomposes the microbial communities into a set of topics (non-mutually-exclusive sub-communities) that compactly represent the distribution of full communities.

Development of Electrochemical Aptasensor for Lung Cancer Diagnostics in Human Blood.

We describe the preparation and characterization of an aptamer-based electrochemical sensor to lung cancer tumor markers in human blood. The highly reproducible aptamer sensing layer with a high density (up to 70% coverage) on the gold electrode was made. Electrochemical methods and confocal laser scanning microscopy were used to study the stability of the aptamer layer structure and binding ability.

Heuristics for unrooted, unranked, and ranked anomaly zones under birth-death models.

Species trees that can generate a nonmatching gene tree topology that is more probable than the topology matching the species tree are said to be in an anomaly zone. We introduce some heuristic approaches to infer whether species trees are in anomaly zones when it is difficult or impossible to compute the entire distribution of gene tree topologies. Here, probabilities of unrooted, unranked, and ranked gene tree topologies under the multispecies coalescent are used.

PRANC: ML species tree estimation from the ranked gene trees under coalescence.

Summary: PRANC computes the Probabilities of RANked gene tree topologies under the multispecies coalescent. A ranked gene tree is a gene tree accounting for the temporal ordering of internal nodes. PRANC can also estimate the maximum likelihood (ML) species tree from a sample of ranked or unranked gene tree topologies.

Probabilities of Unranked and Ranked Anomaly Zones under Birth-Death Models.

A labeled gene tree topology that is more probable than the labeled gene tree topology matching a species tree is called "anomalous." Species trees that can generate such anomalous gene trees are said to be in the "anomaly zone." Here, probabilities of "unranked" and "ranked" gene tree topologies under the multispecies coalescent are considered.