An Analysis of PILOT (Payment in Lieu of Taxes), Windham, Connecticut

This report the history of the "Payment of Lieu of Taxes" (PILOT) fund distrubtion in Windham, CT, the history of the PILOT fund statutes in Connecticut, and a discussion of the impact of tax-exempt properties on Town and the separate Williamntic Fire & Police Service District. The report concludes with a recommendation for PILOT funding going forward.taxes, property, "payment in lieu of taxes", state-owned property, "Windham, CT", "housing authority"

Chemogenomic profiling: Identifying the functional interactions of small molecules in yeast

We demonstrate the efficacy of a genome-wide protocol in yeast that allows the identification of those gene products that functionally interact with small molecules and result in the inhibition of cellular proliferation. Here we present results from screening 10 diverse compounds in 80 genome-wide experiments against the complete collection of heterozygous yeast deletion strains. These compounds include anticancer and antifungal agents, statins, alverine citrate, and dyclonine. In several cases, we identified previously known interactions; furthermore, in each case, our analysis revealed novel cellular interactions, even when the relationship between a compound and its cellular target had been well established. In addition, we identified a chemical core structure shared among three therapeutically distinct compounds that inhibit the ERG24 heterozygous deletion strain, demonstrating that cells may respond similarly to compounds of related structure. The ability to identify on-and-off target effects in vivo is fundamental to understanding the cellular response to small-molecule perturbants

ACUE - Effective Teaching Practices: Module(s) Reflections

This is a collection of ACUE (Association of Colleges and University Educators) implementation and reflection assignments. The Teaching Resource Center partnered with ACUE and the corresponding modules were offered to a set of accepted instructors at CSUSB. These assignments focused on teaching practices designed to enhance the learning experience for both on-ground and online instruction. CSUSB - JHBC Full-time Lecturer, Patrick Flaherty, participated in the ACUE Effective College Instruction certification program from January 2020 thru March 2020, cumulating to a program early-end due to the Coronavirus situation. The attached assignments include reflections from completed modules that include: Leading the first day of class; Planning & Facilitating discussions; Checking for student understanding; Promoting a Civil learning environment; Helping Students persist in their studies, etc

Robust Optimization of Biological Protocols

When conducting high-throughput biological experiments, it is often necessary to develop a protocol that is both inexpensive and robust. Standard approaches are either not cost-effective or arrive at an optimized protocol that is sensitive to experimental variations. Here, we describe a novel approach that directly minimizes the cost of the protocol while ensuring the protocol is robust to experimental variation. Our approach uses a risk-averse conditional value-at-risk criterion in a robust parameter design framework. We demonstrate this approach on a polymerase chain reaction protocol and show that our improved protocol is less expensive than the standard protocol and more robust than a protocol optimized without consideration of experimental variation

RVD2: an ultra-sensitive variant detection model for low-depth heterogeneous next-generation sequencing data

MOTIVATION: Next-generation sequencing technology is increasingly being used for clinical diagnostic tests. Clinical samples are often genomically heterogeneous due to low sample purity or the presence of genetic subpopulations. Therefore, a variant calling algorithm for calling low-frequency polymorphisms in heterogeneous samples is needed. RESULTS: We present a novel variant calling algorithm that uses a hierarchical Bayesian model to estimate allele frequency and call variants in heterogeneous samples. We show that our algorithm improves upon current classifiers and has higher sensitivity and specificity over a wide range of median read depth and minor allele fraction. We apply our model and identify 15 mutated loci in the PAXP1 gene in a matched clinical breast ductal carcinoma tumor sample; two of which are likely loss-of-heterozygosity events

GEMINI: a computationally-efficient search engine for large gene expression datasets

Background Low-cost DNA sequencing allows organizations to accumulate massive amounts of genomic data and use that data to answer a diverse range of research questions. Presently, users must search for relevant genomic data using a keyword, accession number of meta-data tag. However, in this search paradigm the form of the query – a text-based string – is mismatched with the form of the target – a genomic profile. Results To improve access to massive genomic data resources, we have developed a fast search engine, GEMINI, that uses a genomic profile as a query to search for similar genomic profiles. GEMINI implements a nearest-neighbor search algorithm using a vantage-point tree to store a database of n profiles and in certain circumstances achieves an O(log n) expected query time in the limit. We tested GEMINI on breast and ovarian cancer gene expression data from The Cancer Genome Atlas project and show that it achieves a query time that scales as the logarithm of the number of records in practice on genomic data. In a database with 105samples, GEMINI identifies the nearest neighbor in 0.05 sec compared to a brute force search time of 0.6 sec. Conclusions GEMINI is a fast search engine that uses a query genomic profile to search for similar profiles in a very large genomic database. It enables users to identify similar profiles independent of sample label, data origin or other meta-data information

GLAD: A mixed-membership model for heterogeneous tumor subtype classification

MOTIVATION: Genomic analyses of many solid cancers have demonstrated extensive genetic heterogeneity between as well as within individual tumors. However, statistical methods for classifying tumors by subtype based on genomic biomarkers generally entail an all-or-none decision, which may be misleading for clinical samples containing a mixture of subtypes and/or normal cell contamination. RESULTS: We have developed a mixed-membership classification model, called glad, that simultaneously learns a sparse biomarker signature for each subtype as well as a distribution over subtypes for each sample. We demonstrate the accuracy of this model on simulated data, in-vitro mixture experiments, and clinical samples from the Cancer Genome Atlas (TCGA) project. We show that many TCGA samples are likely a mixture of multiple subtypes

Connecticut's Spending Cap: It's History and An Alternative Spending Growth Rule

State spending growth rules and an alternative for Connecticutstate tax policy, spending growth rules, tax and expenditure limits, TELs