Search Results for: expression

Retrieve R "helper" scripts developed for Biostars environment. curl -O http://data.biostarhandbook.com/rnaseq/code/deseq1.r curl -O http://data.biostarhandbook.com/rnaseq/code/deseq2.r curl -O http://data.biostarhandbook. Read More...

Retrieve R "helper" scripts developed for Biostars environment. curl -O http://data.biostarhandbook.com/rnaseq/code/deseq1.r curl -O http://data.biostarhandbook.com/rnaseq/code/deseq2.r curl -O http://data.biostarhandbook. Read More...

Retrieve R "helper" scripts developed for Biostars environment. curl -O http://data.biostarhandbook.com/rnaseq/code/deseq1.r curl -O http://data.biostarhandbook.com/rnaseq/code/deseq2.r curl -O http://data.biostarhandbook. Read More...

Differential Expression Differential expression involves the comparison of normalized expression counts of different samples and the application of statistical measures to identify quantitative changes in gene expression between the different samples. Normalization and Statistical Significance Read More...

06/20/2014 - NCI CCR  http://bioinformatics.nci.nih.gov/training/  and the NIH Library Bioinformatics Support Program http://nihlibrary.nih.gov/Bioinformatics  are partnering to sponsor training on the use of NCBI GEO Datasets to analyze Read More...

Use Partek's implementation of DESeq2. Assign tumor as the numerator and normal as the denominator so that the expression ratio is calculate as average expression for tumor/average expression for normal

Prior to differential expression analysis using the transcript-level expression data, filtering is recommended to remove low expressing transcripts as these may be noise. Several filter options are available in Partek Flow, please refer to the & Read More...

A heatmap depicts numerical data on a color scale and is often used to visualize gene expression. The plot below is constructed using the normalized expression table that contains a subset of genes that were Read More...

03/06/2025 - This class introduces participants to the first steps to differential expression analysis in bulk RNA sequencing which involves filtering out noise from (ie. genes without expression across samples) and performing QC on the gene Read More...

01/22/2025 - This three hour online training covers QIAGEN’s CLC Genomics Workbench enables researchers to analyze NGS data without the use of command line and is a powerful tool for determining differential expression. Read More...

Differential expression analysis is the process of identifying genes that have a significant difference in expression between two or more groups. For many sequencing experiments, regardless of methodology, differential analysis lays the foundation of the Read More...

The primary means of running differential expression in Seurat is through the FindMarkers function. The main usage for this function is as follows: FindMarkers(object,ident.1= ..., ident.2=..., test.use="wilcox", min.pct = 0.01, logfc. Read More...

Next, how do we generate the differential expression results? {{Sdet}} Solution{{Esum}} Rscript $CODE/deseq2.r {{Edet}}

Remember that the deseq2.r script requires that the expression counts table be in csv format. It is currently in tab delimited format as generated by featureCounts. There is also a header line that we Read More...

Final output is typically a rank order list of differentially expressed (DE) genes with expression values and associated p-values. Here are examples from teh programs EdgeR and DESeq2

Plots condense complex and busy tabular data into a form that is easier to interpret. An expression heatmap is a common visualization used in RNA sequencing analysis. A heatmap shows numerical data on a color Read More...

Computing differential expression (DESeq2, edger) Viewing the results (heatmaps) Meaningful results Pathway Analysis RNA Isoform Analysis

Next, what application can we use to obtain an expression counts table? {{Sdet}} Answer{{Esum}} We can use featureCounts if aligned the reads to the genome. We will need our annotation file and either SAM Read More...

Let's create an expression heatmap. How do we do this? Looking at the heatmap, do the treatments (ie. BORED and EXCITED) cluster well together? {{Sdet}} Solution{{Esum}} Rscript $CODE/create_heatmap.r We will Read More...

Let's talk about obtaining expression read counts using an application called featureCounts First let's create a new directory in our ~biostar_class/hbr_uhr folder to store the counts. mkdir hbr_uhr_deg_ Read More...

Differential expression and interpretation of results Brief introduction to gene ontology and pathway analysis

Visualize alignment using IGV Post alignment QC Obtain expression counts

First, create a folder to store the Golden Snidget differential expression analysis results. Name this folder snidget_deg. {{Sdet}} Solution{{Esum}} mkdir snidget_deg {{Edet}}

Below we generate a basic heatmap using the pheatmap package. We use the pheatmap command and include the data that we want to construct a heatmap of as the argument. In the heatmap below, we Read More...

Below we generate a basic heatmap using the pheatmap package. We use the pheatmap command and include the data that we want to construct a heatmap of as the argument. In the heatmap below, we Read More...

01/25/2023 - Bulk RNA-Seq data analysis - learn all about expression counts (raw counts, FPKM, RPKM, TMM, TPM, CPM). Those of you, who are hands-on with RNA-seq, or even simply reading publications on this know there Read More...

10/21/2022 - Single cell chromatin accessibility, measured by ATAC-seq, and single cell gene expression, measured by RNA-seq provide two views on a cell’s state. From chromatin accessibility it is possible to infer information about the Read More...

09/12/2022 - We welcome members of the NIH to join us for a seminar event, covering multiplexed, direct digital gene expression profiling applications utilizing NanoString nCounter expression profiling technology as well as spatial biology discoveries generated Read More...

05/18/2022 - Powerful and Intuitive Gene Expression Visualization Tools to Interpret Biological Signals – Bulk and Single Cell Data The increasing use of genomic technologies, such as RNA-Seq and single cell RNA-Seq, to assess gene expression patterns Read More...

07/15/2021 - Meeting Link: https://cbiit.webex.com/cbiit/j.php?MTID=m933690e1ccdbfd15ae3f75d1cbec3b95 TOPIC: AI in Molecular Data, presented by NVIDIA This talk will describe machine learning and deep Read More...

07/15/2021 - Registration: https://btep.ccr.cancer.gov/classes/ai_three/ Meeting Link: https://cbiit.webex.com/cbiit/j.php?MTID=m933690e1ccdbfd15ae3f75d1cbec3b95 Description: This talk will describe machine learning Read More...

08/11/2020 - Speakers: Nikhita Amod Gogate and Daniel Lyman, George Washington University Data on biomarkers are being collected for a wide range of cancers and stored in data sets around the world. Staying abreast of these Read More...

06/15/2020 - This session will focus on NGS data, multi-omics analysis of array, and sequence data. Participants will work with text files in GeneSpring for NGS gene expression workflow and .vcf files for variant analysis.

07/17/2019 - Learn how to get started on using QIAGEN’s Ingenuity Pathway Analysis (IPA) to quickly identify biological relationships, mechanisms, pathways, functions and diseases most relevant to experimental datasets. IPA is cited in >16,000 Read More...

11/14/2012 -   This is a repeat class for those who couldn't make it into the class on October 9th   Learn the basics of microarray gene expression analysis using Partek Genomics Suite and Partek Pathway. As Read More...

10/09/2012 - Learn the basics of microarray gene expression analysis using Partek Genomics Suite and Partek Pathway. As we walk though hands-on analysis of a cancer dataset, you will learn the principles of experimental design, batch Read More...

After generating and filtering out lower expressing genes from the median ratio normalized expressions data, it is time to perform differential expression analysis to see if there are genes or transcripts (trancripts will be used Read More...

Use Partek Quantification to Model (E/M) algorithm since a gtf annotation is available Uses statistics to assign expression to multi-mappers rather than discarding them Output includes gene and transcript level expression quantifications Summary table Read More...

Normalization of gene expression estimates obtained from the quantification step is important as this will remove technical or non-biological variants in the data such as: Differences in sequencing depth between samples (ie. not all samples Read More...

The script deg.R in b4b_script will be used perform differential expression analysis on the hcc1395 data. This script will use DESeq2 and takes the following as input. Filtered gene expression table, which Read More...

Even without normalization, the filtered expression distribution are very similar between the samples with the median and 25th to 75th percentiles higher in the tumor samples.

Remember that the deseq2.r script requires that the expression counts table be in csv format. It is currently in tab delimited format as generated by featureCounts. There is also a header line that we Read More...

Gene expression table can be generated from the read alignment. Options for generating an expression table. Because there a GTF annotation file is avaialable, this exercise will use the Quantify to annotation model (Partek E/ Read More...

Plots condense complex and busy tabular data into a form that is easier to interpret. An expression heatmap is a common visualization used in RNA sequencing analysis. A heatmap shows numerical data on a color Read More...

Go back to /data/user/hcc1395_b4b. cd /data/user/hcc1395_b4b Create a directory called hcc1395_featurecounts. mkdir hcc1395_featurecounts Go back into /data/user/hcc1395_b4b/hcc1395_hisat2 for this Read More...

The module featureCounts from the subread package will be used to quantify gene expression. In the featureCounts command below: -p: specifies the presence of paired end data. --countReadPairs: specifies to count both reads in a Read More...

Heatmap and dendrogram can reveal clusters of genes whose expression is up or down-regulated under certain biological conditions and from the visualization below, it is clear that there are panels of genes that are upregulated Read More...

Let's create an expression heatmap. How do we do this? Looking at the heatmap, do the treatments (ie. BORED and EXCITED) cluster well together? Solution Rscript $CODE/create_heatmap.r We will need to Read More...

Let's talk about obtaining expression read counts using an application called featureCounts First let's create a new directory in our ~biostar_class/hbr_uhr folder to store the counts. mkdir hbr_uhr_deg_ Read More...

First, create a folder to store the Golden Snidget differential expression analysis results. Name this folder snidget_deg. Solution mkdir snidget_deg

import pandas import seaborn import matplotlib.pyplot as plt counts1=pandas.read_csv("./hbr_uhr_top_deg_normalized_counts.csv", index_col=[0]) seaborn.clustermap(counts1,z_score=0,cmap="viridis", figsize=(5,5)) plt. Read More...

Change into hcc1395_deg from hcc1395_b4b. cd hcc1395_deg List the contents. Use the -1 option to view directory contents 1 item per line. ls -1 The files generated from deg.R are: hcc1395_ Read More...

We want to add the columns gene_symbol and Description from one data table to another data table containing our differential expression results. First, let's load our data. gene_info_fp<-file. Read More...

2024 Date: Tuesday, October 15, 2024 Time and Location: 11 am EST, ZOOM (INVITATION BY LMIG LIST SERVER) Speaker: Dr. Diego Presman (U Buenos Aires) Title: “Insights on Glucocorticoid Receptor Activity Through Live Cell Imaging” Summary: Eucaryotic transcription factors ( Read More...

03/11/2025 - In this class, participants will get hands-on experience with generating and interpreting differential gene expression analysis results from bulk RNA sequencing. In addition, participants will learn to generate common plots used to visualize bulk Read More...

03/04/2025 - Alignment of RNA sequencing data enables researchers to identify where in the genome each sequence came from. However, it does not inform of how many sequences aligned to each genomic feature such as a Read More...

09/11/2024 - Qlucore Omics Explorer is a point-and-click package available to NCI CCR scientists that enables visualization-based analysis of multi-omics data including RNA-seq, scRNA-seq, proteomics, metabolomics, as well as enabling the use of machine learning classification Read More...

One particular critique of differential expression in single cell RNASeq analysis is p-value "inflation," where the p-values get so small that there are far too many genes exist with p-values below 0.05, even after Read More...

01/24/2024 - Dear colleagues,   Please join us on Wed., Jan. 24 when Dr. Avi Ma’ayan from the Icahn School of Medicine at Mount Sinai will demonstrate how to use these tools to access hundreds of thousands Read More...

01/03/2024 - on Wednesday, January 3rd at noon in Building 41, Conference Room C507/C509 and online. In-person attendance is encouraged.  Dr. Larson's research is focused on understanding gene expression in eukaryotic Read More...

Prior to differential expression analysis, we need to generate a design.csv file that contains the samples and their corresponding treatment conditions. Note that csv stands for comma separated value so the columns in these Read More...

Let's now create a gene expression heatmap for results generated using the classification based approach. We have our results.csv and design.csv file in our salmon directory so we just need to do Read More...

Below we generate the basic heatmap using the pheatmap package. It is simple, just use the pheatmap command and include the data that we want to construct a heatmap of as the argument. In the Read More...

09/22/2021 - Registration is required. During this upcoming webinar, Dr. Yanjun Qi will demonstrate AttentiveChrome, an attention-based deep learning approach that uses a unified architecture to model and interpret interactions and dependencies among the chromatin factors Read More...

04/21/2021 - Registration Session Description QIAGEN’s CLC Genomics Workbench enables researchers to analyze NGS data without the use of command line and is a powerful tool for determining differential expression and for variant calling. In Read More...

01/27/2021 - Please plan to attend the Earl Stadtman Investigator Program search seminar by: Qian Zhu, Ph.D. Dana Farber Cancer Institute/Boston Children's Hospital Dr. Zhu's research interests include: single-cell genomics; spatial transcriptomics; Read More...

02/20/2020 - Learn how to easily analyze your gene expression data yourself - using Qlucore Omics Explorer NCI/CCR:To get access to Qlucore, put a request into NCI at Your Service under Get Help https:// Read More...

Prior to differential expression analysis, we need to generate a design.csv file that contains the samples and their corresponding treatment conditions. Note that csv stands for comma separated value so the columns in these Read More...

{{Sdet}}{{Ssum}}Gene expression by microarray{{Esum}} CLC Genomics Workbench What file types can I start my analysis with? Affymetrix Gene Chip (CHP, NetAFFx, CEL) Illumina BeadChip TSV CSV Partek Flow What file types can Read More...

We will use the R helper scripts that we used before. cat 22simple_counts.txt | Rscript deseq2.r 3x3 > 22results_deseq2.txt The file 22results_deseq2.txt contains the genes sorted by their adjusted Read More...

We will use the R helper scripts that we used before. cat 22simple_counts.txt | Rscript deseq2.r 3x3 > 22results_deseq2.txt The file 22results_deseq2.txt contains the genes sorted by their adjusted Read More...

We will use the R helper scripts that we used before. cat 22simple_counts.txt | Rscript deseq2.r 3x3 > 22results_deseq2.txt The file 22results_deseq2.txt contains the genes sorted by their adjusted Read More...

03/12/2019 - https://cbiit.webex.com/recordingservice/sites/cbiit/recording/3d246d9ba88a48f188e07a5f60fef3b3/playback

1. Introduction and Learning Objectives This tutorial has been designed to demonstrate common secondary analysis steps in a scRNA-Seq workflow. We will start with a merged Seurat Object with multiple data layers representing multiple samples that Read More...

02/24/2025 - AI Club is a weekly meeting that explores various topics relating to AI and deep learning in biomedical sciences, typically in a seminar, workshop, or journal club format. AI Club is intended to be Read More...

10/10/2024 - This introductory lecture will provide an overview of bulk RNA-Seq technology, its various application and shortcomings, as well as detailing the steps involved in analyzing the resulting data. The talk is aimed at those Read More...

10/18/2023 - This October session of the BTEP Coding club will feature a tutorial on how to access data from GEO as well as how to submit data to GEO.     

Next, we need to generate the counts (ie. number of reads that map to a transcript). But first, change back into the ~/biostar_class/snidget folder and then take a moment to think about how Read More...

Most RNASEQ techniques deal with count data. The reads are mapped to a reference and the number of reads mapped to each gene/transcript is counted Read counts are roughly proportional to gene-length and abundance Read More...

An example of a counts matrix for RNASEQ data.

After alignment of sequencing data to genome, we will need to count how many reads aligned to which gene. Using the tool featureCounts, we were able to do this. This tool takes as input our Read More...

11/17/2021 - In this talk, Dr. David Kepplinger will describe the detrimental effects of “data-artifacts,” specifically as they relate to biomarker discovery and related feature selection techniques. He will also discuss a novel method for reliably Read More...

08/29/2019 - https://cbiit.webex.com/recordingservice/sites/cbiit/recording/361655cd97c049da80df811be91adc04/playback

10/02/2012 - Microarray Technology and Preprocessing Quality Control Normalization Using MAS5 and RMA Filtering Batch Effect Correction Basic Statistical Tests for Differentially Expressed Genes T-test ANOVA SAM Calculating False Discovery Rate Principal Components Analysis and Clustering Read More...

Research Mission The goal of OMAL’s research is to understand molecular mechanisms driving carcinogenesis and the reversal of this process through treatment, by utilization and advancement of optical microscopy techniques. These techniques include multiplex Read More...

Employing spatial biology techniques enables acquisition of transcript and protein data from intact tissue sections, and in turn, spatial distribution information and cellular interaction patterns are revealed.

Employing spatial biology techniques enables acquisition of transcript and protein data from intact tissue sections, and in turn, spatial distribution information and cellular interaction patterns are revealed.

Techniques The Laboratory of Cancer Biology and Genetics Microscopy Core houses multiple systems that can be used to analyze cell structure, protein expression, and cell dynamics using immunofluorescence. These include inverted epifluorescence microscopes, a confocal Read More...

2024 Coutinho, L. L., Femino, E. L., Gonzalez, A. L., Moffat, R. L., Heinz, W. F., Cheng, R. Y. S., Lockett, S. J., Rangel, M. C., Ridnour, L. A. & Wink, D. A. NOS2 and Read More...

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We are a bioinformatics team within the Center for Biomedical Informatics and Information Technology’s (CBIIT’s) Cancer Informatics Branch (CIB)—soon to be referred to as the Informatics and Data Science (IDS) Program. Headed Read More...

The Genomics Technology Laboratory is an integrated, high-throughput molecular biology laboratory focusing on the development of genetics and genomics technologies, data analysis, and information management tools, in support of CCR Investigators. The laboratory develops integrated Read More...

The Genomics and Pharmacology Facility is part of the NCI's Center for Cancer Research (CCR), within the Developmental Therapeutics Branch. Its mission is to manage and assess molecular interaction data obtained through multiple platforms, increase Read More...

The NIH Center for Human Immunology, Inflammation, and Autoimmunity (CHI) is a trans-NIH resource whose mission is to provide a collaborative hub of advanced translational immunology for NIH clinical and pre-clinical studies. This uniquely structured Read More...

What is Xenium? Xenium is a high-resolution, imaging-based in situ spatial profiling technology from 10x Genomics that allows for simultaneous expression analysis of RNA targets (currently in range of 100’s) within the same tissue section. Read More...

The Genomics Laboratory (formerly Laboratory of Molecular Technology) is an integrated, high-throughput molecular biology laboratory focusing on the development of genetics and genomics technologies, together with associated laboratory automation systems, data analysis, and information management Read More...

CREx News & Updates July 2021   Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More NIH Collaborative Research Exchange (CREx) News Site Spotlight FACILITY HIGHLIGHTS Learn more about services from the NHLBI Read More...

Mass Spectrometry Section of the Collaborative Protein Technology Resource (Bldg. 37) Core Capabilities: Identification of proteins in complexes, organelles, subcellular fractions, or fluids. Global relative protein quantitation. Quantitation by isotopic labeling of cells in culture (SILAC) Read More...

The Flow Cytometry Core (LGI) offers established technologies to support studies using flow cytometry and cell sorting. Established Technologies Applications that run on FACS Caliburs include: Immunophenotyping (up to 4-color), Intracellular markers, including cytokines and Read More...

Radiation Oncology Branch is part of CCR. Bioinformatics core is a collaborative resource to support ROB branch and provide service to ROB investigators from NCI and other Institutes access to new technologies, bioinformatics, statistical analysis Read More...

The Bloomington Drosophila Stock Center (BDSC) collects, maintains, and distributes genetically defined strains of Drosophila melanogaster for research and education. The BDSC supports a large, worldwide community of scientists using Drosophila as a model organism Read More...

[embed]https://youtu.be/yTl1Q0D7aZ0[/embed] 10x Genomics' supports multiple cancer research areas from single nucleotide and structural variant detection to single cell whole transcriptome gene expression analysis of thousands of individual Read More...

CREx Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More New Resources on CREx NCI CLIA Molecular Diagnostics Laboratory (CMDL) The NCI CMDL is available to assist all Read More...

HALO HALO is a powerful 2D image analysis tool with AI capabilities to perform annotations and analysis on bright-field and immunofluorescent images for digital pathology and numerous other applications.  It offers a set of algorithms Read More...

2025 Sebastian R, Sun EG, Fedkenheuer M, Fu H, Jung S, Thakur BL, Redon CE, Pegoraro G, Tran AD, Gross JM, Mosavarpour S, Kusi NA, Ray A, Dhall A, Pongor LS, Casellas R, Aladjem MI. Mechanism Read More...

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The CCR Genomics Core is located in Building 41 on the NIH Bethesda campus. The primary goal of the Core is to provide investigators from CCR/NCI and other NIH Institutes access to genomic technologies and Read More...

NISC’s role within NHGRI, and more broadly across NIH, aims to advance genome sequencing and its many applications, with a goal not simply to produce sequence data, but to produce the infrastructure required to Read More...

Protein Characterization Laboratory (PCL) offers various technologies to CCR investigators to characterize proteins and metabolites. The laboratory develops and applies state-of-the-art analytical technologies, primarily mass spectrometry, liquid chromatography, and Surface Plasmon Resonance (SPR), to advance Read More...

The Biopharmaceutical Development Program (BDP) provides resources for the development of investigational biological agents. The BDP supports feasibility through development and Phase I/II cGMP manufacturing plus regulatory documentation.The BDP was established in 1993. We Read More...

CREx Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More New NIH Resource Resources Advance your research with the NIH Mouse Imaging Facility (MIF) The NIH Mouse Imaging Read More...

The CLIA Molecular Diagnostics Laboratory (CMDL) provides an array of services for groups at the NIH Clinical Center, Fort Detrick, and Hood College, among others. They support cancer- and disease-related research by making Read More...

CREx Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More New NIH Resource Resources Derive Greater Insights and Accelerate your Research Using Bioinformatic Tools! CREx is an NIH Read More...

The National Cancer Institute (NCI) is developing a national repository of Patient-Derived Models (PDMs) comprised of patient-derived xenografts (PDXs), patient-derived organoids (PDOrg), and in vitro patient-derived tumor cell cultures (PDCs) and cancer-associated fibroblasts (CAFs). These Read More...

The introduction of DNA sequencing instruments capable of producing millions of DNA sequence reads in a single run has profoundly altered the landscape of genetics and cancer biology. Complex questions can now be answered at Read More...

Supplemental Technology Award Review System (STARS) Overview STARS Request Form STARS System The Supplemental Technology Award Review System (STARS) is a web-based interface for submission and review of S&S supplement requests by CCR Read More...

CREx News & Updates October 2021 Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More NIH Collaborative Research Exchange (CREx) News Site Spotlight FACILITY HIGLIGHTS Learn more about services from the CPTR Read More...

The Spatial Imaging Technology Resource (formerly the Nanoscale Protein Analysis Section of the Collaborative Protein Technology Resource or CPTR) provides expertise and service in state-of-the-art protein analysis technologies to advance CCR research in basic discovery Read More...

The facilities at AIM are available for use by the entire NIH intramural research community. While we welcome users with any size imaging project, AIM specializes in large, yearlong (or longer), collaborative research efforts with Read More...

Our Team Tatiana S. Karpova Ph.D.Core Headkarpovat@nih.govBuilding 41, Room C615240-760-6637 David A. Ball Ph.D.Core Biologistballa@nih.govBuilding 41, Room B114D240-760-6577 Mohamadreza Fazel, Ph.D.Core Biologistmohamadreza. Read More...

2016-2024 Publications using images obtained in OMC

General Usage Policies Principal investigators should read this document and sign it. PI’s/postdocs should attach a short-written summary of the project to the signed doc. If the project changes, Read More...

2024 L. Balagopalan, T. Moreno, H. Qin, B. C. Angeles, T. Kondo, J. Yi, K. M. McIntire, N. Alvinez, S. Pallikkuth, M. E. Lee, H. Yamane, A. D. Tran, P. Youkharibache, R. E. Cachau, N. Taylor, Read More...

Software LAS Leica Application Suite X (LAS X) is the one software platform for all Leica microscopes: It integrates confocal, wide field, stereo, super-resolution, and light-sheet instruments from Leica Microsystems. MetaMorph The MetaMorph® Microscopy Automation Read More...

Stephen Lockett, Ph.D. Director, OMAL locketts@nih.gov 301-846-5515 Valentin Magidson, Ph.D. Scientist magidsonv@mail.nih.gov 301-846-6092 Will Heinz, Ph.D. Scientist heinzwf@nih.gov 301-846-1239 David Read More...

General Microscopy Resources Confocal Listserv Email discussion list focused on confocal microscopy, but also including topics on fluorescence microscopy and digital imaging. MicroscopyU Online learning platform by Nikon.  An online source for Microscopy education. Leica Read More...

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