Molecular Biology Commons^™

Libraries At The University Of Massachusetts Amherst: Seeking An International Perspective, Maxine G. Schmidt

Maxine G Schmidt

Presentation delivered to librarians in China, Japan and South Korea as part of my sabbatical research on the use of libraries by Asian students in their home countries.

Integrative Bayesian Analysis Of High-Dimensional Multi-Platform Genomics Data, Wenting Wang, Veerabhadran Baladandayuthapani, Jeffrey S. Morris, Bradley M. Broom, Ganiraju C. Manyam, Kim-Anh Do

Jeffrey S. Morris

Motivation: Analyzing data from multi-platform genomics experiments combined with patients’ clinical outcomes helps us understand the complex biological processes that characterize a disease, as well as how these processes relate to the development of the disease. Current integration approaches that treat the data are limited in that they do not consider the fundamental biological relationships that exist among the data from platforms.

Statistical Model: We propose an integrative Bayesian analysis of genomics data (iBAG) framework for identifying important genes/biomarkers that are associated with clinical outcome. This framework uses a hierarchical modeling technique to combine the data obtained from multiple platforms …

Hslic Fall 2012 Scholarship Committee Report, Ann Jordan

Ann Jordan

No abstract provided.

Arcane Secrets Of The Umass Libraries, Maxine G. Schmidt

Maxine G Schmidt

No abstract provided.

Science Boot Camp For Librarians: Cpd On A Shoestring, Maxine G. Schmidt, Rebecca Reznik-Zellen

Maxine G Schmidt

Science Boot Camp for Librarians was envisioned as a casual but intensive immersion event into selected scientific subjects that employ networked computing capabilities for research and collaboration. The goal of the event is to provide librarians with networking opportunities, but more importantly, to give them some of the context and ocabulary of a discipline to enable them to better engage faculty and research scientists with regard to escience. A half-day is devoted to each of three topics chosen for that year’s camp. A local faculty member provides an overview of the research area, and a second describes a single project …

Ppar Agonists Down-Regulate The Expression Of Atp10c Mrna During Adipogenesis, A Peretich, Maria Cekanova Ms, Rndr, Phd, S Hurst, Sj Baek, Madhu Dahr

Maria Cekanova MS, RNDr, PhD

No abstract provided.

E-Science @ Umass: Anticipating And Supporting E-Science Activities At The University Of Massachusetts, Maxine G. Schmidt, Rebecca Reznik-Zellen

Maxine G Schmidt

In March of 2008 an Ad Hoccommittee of Science Librarians from the University of Massachusetts Five Campus System convened to discuss the challenges of e-science and prepare the Libraries for their role in e-science initiatives. Three primary outcomes intended to support e-science activities emerged from the work of the Ad Hoc committee.

E-Science @ The University Of Massachusetts, Maxine G. Schmidt, Rebecca Reznik-Zellen, Raquel Rivera, Cecilia P. Mullen

Maxine G Schmidt

e-Science @ the University of Massachusetts Abstract: What is e-Science and how can libraries and librarians support it? The University of Massachusetts takes a proactive approach to support network-enabled research on its campuses and provides examples where e-Science is already at work. Statement: “e-Science” is a term commonly used to describe research in a networked environment, a growing trend not only in the sciences, but the arts and humanities as well. e-Science creates both opportunities and challenges for academic libraries. The opportunities lie in leveraging the basic skill set that libraries and librarians already possess: the knowledge of and practical …

Umass Libraries 2009, Maxine G. Schmidt

Maxine G Schmidt

No abstract provided.

Gene Alterations By Peroxisome Proliferator-Activated Receptor Gamma Agonists In Human Colorectal Cancer Cells, Maria Cekanova, J Yuan, X Li, K B. Kim, Seung J. Baek

Maria Cekanova MS, RNDr, PhD

The peroxisome proliferator-activated receptor gamma (PPARgamma) is a nuclear transcription factor that controls the genes involved in metabolism and carcinogenesis. In the present study, we examined the alteration of gene expression in HCT-116 human colorectal cancer cells by PPARgamma agonists: MCC-555 (5 microM), rosiglitazone (5 microM), and 15-deoxy-Delta12,14-prostaglandin J2 (1 microM). The long-oligo microarray data revealed a list of target genes commonly induced (307 genes) and repressed (32 genes) by tested PPARgamma agonists. These genes were analyzed by Onto-Express software and KEGG pathway analysis and revealed that PPARgamma agonists are involved in cell proliferation, focal adhesion, and several signaling pathways. …

Microproteomics: Analysis Of Protein Diversity In Small Samples, Howard B. Gutstein, Jeffrey S. Morris, Suresh P. Annangudi, Jonathan V. Sweedler

Jeffrey S. Morris

Proteomics, the large-scale study of protein expression in organisms, offers the potential to evaluate global changes in protein expression and their post-translational modifications that take place in response to normal or pathological stimuli. One challenge has been the requirement for substantial amounts of tissue in order to perform comprehensive proteomic characterization. In heterogeneous tissues, such as brain, this has limited the application of proteomic methodologies. Efforts to adapt standard methods of tissue sampling, protein extraction, arraying, and identification are reviewed, with an emphasis on those appropriate to smaller samples ranging in size from several microliters down to single cells. The …

Important, But Odd And Obscure, Reasons To Use The Library, Maxine G. Schmidt

Maxine G Schmidt

No abstract provided.

Statistical Issues In Proteomic Research, Jeffrey S. Morris

Jeffrey S. Morris

No abstract provided.

Pre-Processing Mass Spectrometry Data, Kevin R. Coombes, Keith A. Baggerly, Jeffrey S. Morris

Jeffrey S. Morris

No abstract provided.

Laser Capture Sampling And Analytical Issues In Proteomics, Howard Gutstein, Jeffrey S. Morris

Jeffrey S. Morris

Proteomics holds the promise of evaluating global changes in protein expression and post-translational modificaiton in response to environmental stimuli. However, difficulties in achieving cellular anatomic resolution and extracting specific types of proteins from cells have limited the efficacy of these techniques. Laser capture microdissection has provided a solution to the problem of anatomical resolution in tissues. New extraction methodologies have expanded the range of proteins identified in subsequent analyses. This review will examine the application of laser capture microdissection to proteomic tissue sampling, and subsequent extraction of these samples for differential expression analysis. Statistical and other quantitative issues important for …

Alternative Probeset Definitions For Combining Microarray Data Across Studies Using Different Versions Of Affymetrix Oligonucleotide Arrays, Jeffrey S. Morris, Chunlei Wu, Kevin R. Coombes, Keith A. Baggerly, Jing Wang, Li Zhang

Jeffrey S. Morris

Many published microarray studies have small to moderate sample sizes, and thus have low statistical power to detect significant relationships between gene expression levels and outcomes of interest. By pooling data across multiple studies, however, we can gain power, enabling us to detect new relationships. This type of pooling is complicated by the fact that gene expression measurements from different microarray platforms are not directly comparable. In this chapter, we discuss two methods for combining information across different versions of Affymetrix oligonucleotide arrays. Each involves a new approach for combining probes on the array into probesets. The first approach involves …

Prepms: Tof Ms Data Graphical Preprocessing Tool, Yuliya V. Karpievitch, Elizabeth G. Hill, Adam J. Smolka, Jeffrey S. Morris, Kevin R. Coombes, Keith A. Baggerly, Jonas S. Almeida

Jeffrey S. Morris

We introduce a simple-to-use graphical tool that enables researchers to easily prepare time-of-flight mass spectrometry data for analysis. For ease of use, the graphical executable provides default parameter settings experimentally determined to work well in most situations. These values can be changed by the user if desired. PrepMS is a stand-alone application made freely available (open source), and is under the General Public License (GPL). Its graphical user interface, default parameter settings, and display plots allow PrepMS to be used effectively for data preprocessing, peak detection, and visual data quality assessment.

Some Statistical Issues In Microarray Gene Expression Data, Matthew S. Mayo, Byron J. Gajewski, Jeffrey S. Morris

Jeffrey S. Morris

In this paper we discuss some of the statistical issues that should be considered when conducting experiments involving microarray gene expression data. We discuss statistical issues related to preprocessing the data as well as the analysis of the data. Analysis of the data is discussed in three contexts: class comparison, class prediction and class discovery. We also review the methods used in two studies that are using microarray gene expression to assess the effect of exposure to radiofrequency (RF) fields on gene expression. Our intent is to provide a guide for radiation researchers when conducting studies involving microarray gene expression …

Probability Of Real -Time Detection Vs Probability Of Infection For Aerosolized Biowarfare Agents: A Model Study., Alexander G. Sabelnikov, Vladimir Zhukov, C Ruth Kempf

Alexander G Sabelnikov

No abstract provided.

Shrinkage Estimation For Sage Data Using A Mixture Dirichlet Prior, Jeffrey S. Morris, Keith A. Baggerly, Kevin R. Coombes

Jeffrey S. Morris

Serial Analysis of Gene Expression (SAGE) is a technique for estimating the gene expression profile of a biological sample. Any efficient inference in SAGE must be based upon efficient estimates of these gene expression profiles, which consist of the estimated relative abundances for each mRNA species present in the sample. The data from SAGE experiments are counts for each observed mRNA species, and can be modeled using a multinomial distribution with two characteristics: skewness in the distribution of relative abundances and small sample size relative to the dimension. As a result of these characteristics, a given SAGE sample will fail …

An Introduction To High-Throughput Bioinformatics Data, Keith A. Baggerly, Kevin R. Coombes, Jeffrey S. Morris

Jeffrey S. Morris

High throughput biological assays supply thousands of measurements per sample, and the sheer amount of related data increases the need for better models to enhance inference. Such models, however, are more effective if they take into account the idiosyncracies associated with the specific methods of measurement: where the numbers come from. We illustrate this point by describing three different measurement platforms: microarrays, serial analysis of gene expression (SAGE), and proteomic mass spectrometry.

Bayesian Mixture Models For Gene Expression And Protein Profiles, Michele Guindani, Kim-Anh Do, Peter Mueller, Jeffrey S. Morris

Jeffrey S. Morris

We review the use of semi-parametric mixture models for Bayesian inference in high throughput genomic data. We discuss three specific approaches for microarray data, for protein mass spectrometry experiments, and for SAGE data. For the microarray data and the protein mass spectrometry we assume group comparison experiments, i.e., experiments that seek to identify genes and proteins that are differentially expressed across two biologic conditions of interest. For the SAGE data example we consider inference for a single biologic sample.

Analysis Of Mass Spectrometry Data Using Bayesian Wavelet-Based Functional Mixed Models, Jeffrey S. Morris, Philip J. Brown, Keith A. Baggerly, Kevin R. Coombes

Jeffrey S. Morris

In this chapter, we demonstrate how to analyze MALDI-TOF/SELDITOF mass spectrometry data using the wavelet-based functional mixed model introduced by Morris and Carroll (2006), which generalizes the linear mixed models to the case of functional data. This approach models each spectrum as a function, and is very general, accommodating a broad class of experimental designs and allowing one to model nonparametric functional effects for various factors, which can be conditions of interest (e.g. cancer/normal) or experimental factors (blocking factors). Inference on these functional effects allows us to identify protein peaks related to various outcomes of interest, including dichotomous outcomes, categorical …

Improved Peak Detection And Quantification Of Mass Spectrometry Data Acquired From Surface-Enhanced Laser Desorption And Ionization By Denoising Spectra With The Undecimated Discrete Wavelet Transform, Kevin R. Coombes, Spiros Tsavachidis, Jeffrey S. Morris, Keith A. Baggerly, Henry M. Kuerer

Jeffrey S. Morris

Background: Mass spectrometry, especially surface enhanced laser desorption and ionization (SELDI) is increasingly being used to find disease-related proteomic patterns in complex mixtures of proteins derived from tissue samples or from easily obtained biological fluids such as serum, urine, or nipple aspirate fluid. Questions have been raised about the reproducibility and reliability of peak quantifications using this technology. For example, Yasui and colleagues opted to replace continuous measures of the size of a peak by a simple binary indicator of its presence or absence in their analysis of a set of spectra from prostate cancer patients.

Methods: We collected nipple …

Pooling Information Across Different Studies And Oligonucleotide Microarray Chip Types To Identify Prognostic Genes For Lung Cancer., Jeffrey S. Morris, Guosheng Yin, Keith A. Baggerly, Chunlei Wu, Li Zhang

Jeffrey S. Morris

Our goal in this work is to pool information across microarray studies conducted at different institutions using two different versions of Affymetrix chips to identify genes whose expression levels offer information on lung cancer patients’ survival above and beyond the information provided by readily available clinical covariates. We combine information across chip types by identifying “matching probes” present on both chips, and then assembling them into new probesets based on Unigene clusters. This method yields comparable expression level quantifications across chips without sacrificing much precision or significantly altering the relative ordering of the samples. We fit a series of multivariable …

Expression Of G-Protein Inwardly Rectifying Potassium Channels (Girks) In Lung Cancer Cell Lines, Howard Plummer 3rd, Madhu Dhar, Maria Cekanova Ms, Rndr, Phd, Hildegard Schuller

Maria Cekanova MS, RNDr, PhD

BACKGROUND: Previous data from our laboratory has indicated that there is a functional link between the beta-adrenergic receptor signaling pathway and the G-protein inwardly rectifying potassium channel (GIRK1) in human breast cancer cell lines. We wanted to determine if GIRK channels were expressed in lung cancers and if a similar link exists in lung cancer. METHODS: GIRK1-4 expression and levels were determined by reverse transcription polymerase chain reaction (RT-PCR) and real-time PCR. GIRK protein levels were determined by western blots and cell proliferation was determined by a 5-bromo-2'-deoxyuridine (BrdU) assay. RESULTS: GIRK1 mRNA was expressed in three of six small …

Serum Proteomics Profiling: A Young Technology Begins To Mature, Kevin R. Coombes, Jeffrey S. Morris, Jianhua Hu, Sarah R. Edmondson, Keith A. Baggerly

Jeffrey S. Morris

No abstract provided.

Signal In Noise: Evaluating Reported Reproducibility Of Serum Proteomic Tests For Ovarian Cancer, Keith A. Baggerly, Jeffrey S. Morris, Sarah R. Edmonson, Kevin R. Coombes

Jeffrey S. Morris

Proteomic profi ling of serum initially appeared to be dramatically effective for diagnosis of early-stage ovarian cancer, but these results have proven diffi cult to reproduce. A recent publication reported good classifi cation in one dataset using results from training on a much earlier dataset, but the authors have since reported that they did not perform the analysis as described. We examined the reproducibility of the proteomic patterns across datasets in more detail. Our analysis reveals that the pattern that enabled successful classifi cation is biologically implausible and that the method, properly applied, does not classify the data accurately. We …

High-Resolution Serum Proteomic Patterns For Ovarian Cancer Detection, Keith A. Baggerly, Sarah R. Edmonson, Jeffrey S. Morris, Kevin R. Coombes

Jeffrey S. Morris

No abstract provided.

A Hidden Markov Model Capable Of Predicting And Discriminating Β-Barrel Outer Membrane Proteins, Pantelis G. Bagos, Theodore D. Liakopoulos, Ioannis C. Spyropoulos, Stavros J. Hamodrakas

Pantelis Bagos

BACKGROUND: Integral membrane proteins constitute about 20-30% of all proteins in the fully sequenced genomes. They come in two structural classes, the alpha-helical and the beta-barrel membrane proteins, demonstrating different physicochemical characteristics, structure and localization. While transmembrane segment prediction for the alpha-helical integral membrane proteins appears to be an easy task nowadays, the same is much more difficult for the beta-barrel membrane proteins. We developed a method, based on a Hidden Markov Model, capable of predicting the transmembrane beta-strands of the outer membrane proteins of gram-negative bacteria, and discriminating those from water-soluble proteins in large datasets. The model is trained …