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Articles 1 - 30 of 38
Full-Text Articles in Medical Molecular Biology
Identification And Characterisation Of The Early Differentiating Cells In Neural Differentiation Of Human Embryonic Stem Cells, Thamil Selvee Ramasamy
Identification And Characterisation Of The Early Differentiating Cells In Neural Differentiation Of Human Embryonic Stem Cells, Thamil Selvee Ramasamy
Thamil Selvee Ramasamy
One of the challenges in studying early differentiation of human embryonic stem cells (hESCs) is being able to discriminate the initial differentiated cells from the original pluripotent stem cells and their committed progenies. It remains unclear how a pluripotent stem cell becomes a lineage-specific cell type during early development, and how, or if, pluripotent genes, such as Oct4 and Sox2, play a role in this transition. Here, by studying the dynamic changes in the expression of embryonic surface antigens, we identified the sequential loss of Tra-1-81 and SSEA4 during hESC neural differentiation and isolated a transient Tra-1-81(-)/SSEA4(+) (TR-/S4+) cell population …
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
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 …
Science Boot Camp For Librarians: Cpd On A Shoestring, Maxine G. Schmidt, Rebecca Reznik-Zellen
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
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
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
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 …
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
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
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 …
Sera Of Iga Nephropathy Patients Contain A Heterogeneous Population Of Relatively Cationic Alpha-Heavy Chains, Onn Haji Hashim
Sera Of Iga Nephropathy Patients Contain A Heterogeneous Population Of Relatively Cationic Alpha-Heavy Chains, Onn Haji Hashim
Onn Haji Hashim
Sera of IgA nephropathy (IgAN) patients and normal subjects were analysed by two-dimensional (2-D) gel electrophoresis. Densitometric analysis of the 2-D gels of IgAN patients and normal subjects revealed that their protein maps were comparable. There was no shift of pI values in the major alpha-heavy chain spots. However, the volume of the alpha-heavy chain bands were differently distributed. Distribution was significantly lower at the anionic region in IgAN patients (mean anionic:cationic ratio of 1.184 +/- 0.311) as compared to normal healthy controls (mean anionic:cationic ratio of 2.139 +/- 0.538). Our data are in support of the previously reported findings …
Statistical Issues In Proteomic Research, Jeffrey S. Morris
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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 …
Quality Control And Peak Finding For Proteomics Data Collected From Nipple Aspirate Fluid Using Surface Enhanced Laser Desorption And Ionization., Jeffrey S. Morris, Kevin R. Coombes, Herbert A. Fritsche, Charlotte Clarke, Jeng-Neng Chen, Keith A. Baggerly, Lian-Chun Xiao, Mien-Chie Hung, Henry M. Kuerer
Quality Control And Peak Finding For Proteomics Data Collected From Nipple Aspirate Fluid Using Surface Enhanced Laser Desorption And Ionization., Jeffrey S. Morris, Kevin R. Coombes, Herbert A. Fritsche, Charlotte Clarke, Jeng-Neng Chen, Keith A. Baggerly, Lian-Chun Xiao, Mien-Chie Hung, Henry M. Kuerer
Jeffrey S. Morris
Background: Recently, researchers have been using mass spectroscopy to study cancer. For use of proteomics spectra in a clinical setting, stringent quality-control procedures will be needed.
Methods: We pooled samples of nipple aspirate fluid from healthy breasts and breasts with cancer to prepare a control sample. Aliquots of the control sample were used on two spots on each of three IMAC ProteinChip® arrays (Ciphergen Biosystems, Inc.) on 4 successive days to generate 24 SELDI spectra. In 36 subsequent experiments, the control sample was applied to two spots of each ProteinChip array, and the resulting spectra were analyzed to determine how …
Multiple Luteinizing Hormone Receptor (Lhr) Protein Variants, Interspecies Reactivity Of Anti-Lhr Mab Clone 3b5, Subcellular Localization Of Lhr In Human Placenta, Pelvic Floor And Brain, And Possible Role For Lhr In The Development Of Abnormal Pregnancy, Pelvic Floor Disorders And Alzheimer's Disease, A Bukovsky, K Indrapichate, H Fujiwara, Maria Cekanova Ms, Rndr, Phd, Me Ayala, R Dominguez, Mr Caudle, J Wimalsena, Rf Elder, P Copas, Jf Foster, Ri Fernando, Dc Henley, Nb Upadhyaya
Multiple Luteinizing Hormone Receptor (Lhr) Protein Variants, Interspecies Reactivity Of Anti-Lhr Mab Clone 3b5, Subcellular Localization Of Lhr In Human Placenta, Pelvic Floor And Brain, And Possible Role For Lhr In The Development Of Abnormal Pregnancy, Pelvic Floor Disorders And Alzheimer's Disease, A Bukovsky, K Indrapichate, H Fujiwara, Maria Cekanova Ms, Rndr, Phd, Me Ayala, R Dominguez, Mr Caudle, J Wimalsena, Rf Elder, P Copas, Jf Foster, Ri Fernando, Dc Henley, Nb Upadhyaya
Maria Cekanova MS, RNDr, PhD
Distinct luteinizing hormone receptor (LHR) protein variants exist due to the posttranslational modifications. Besides ovaries, LHR immunoreactivity (LHRI) was also found in other tissues, such as the brain, fallopian tube, endometrium, trophoblast and resident tissue macrophages. The 3B5 mouse monoclonal antibody was raised against purified rat LHR. In rat, porcine and human ovaries, the 3B5 identified six distinct LHR bands migrating at approximately 92, 80, 68, 59, 52 and 48 kDa. Characteristic LHRI was detected in rat, human and porcine corpora lutea. During cellular differentiation, subcellular LHR distribution changed from none to granular cytoplasmic, perinuclear, surface, nuclear and no staining. …
A Comprehensive Approach To The Analysis Of Maldi-Tof Proteomics Spectra From Serum Samples., Keith A. Baggerly, Jeffrey S. Morris, Jing Wang, David Gold, Lian-Chun Xiao, Kevin R. Coombes
A Comprehensive Approach To The Analysis Of Maldi-Tof Proteomics Spectra From Serum Samples., Keith A. Baggerly, Jeffrey S. Morris, Jing Wang, David Gold, Lian-Chun Xiao, Kevin R. Coombes
Jeffrey S. Morris
For our analysis of the data from the First Annual Proteomics Data Mining Conference, we attempted to discriminate between 24 disease spectra (group A) and 17 normal spectra (group B). First, we processed the raw spectra by (i) correcting for additive sinusoidal noise (periodic on the time scale) affecting most spectra, (ii) correcting for the overall baseline level, (iii) normalizing, (iv) recombining fractions, and (v) using variable- width windows for data reduction. Also, we identified a set of polymeric peaks (at multiples of 180.6 Da) that is present in several normal spectra (B1–B8). After data processing, we found the intensities …