Search Results for: force spectroscopy

To begin plotting, let's load our tidyverse library. #load libraries library(tidyverse) # Tidyverse automatically loads ggplot2 ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.3 ✔ readr 2.1.4 ## ✔ forcats 1.0.0 ✔ stringr 1.5.0 ## ✔ ggplot2 3.4.4 ✔ tibble 3.2.1 ## ✔ lubridate 1.9.3 ✔ tidyr 1.3.0 ## ✔ purrr 1.0.2 ## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ── ## ✖ dplyr:: Read More...

We do not need to load the dplyr package separately, as it is a core tidyverse package. If you need to install and load only dplyr , use install.packages("dplyr") and library(dplyr) . Read More...

In this lesson, we are continuing with the package dplyr . We do not need to load the dplyr package separately, as it is a core tidyverse package. Again, if you need to install and load Read More...

This lesson will use some functions from the tidyverse. library(tidyverse) ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ✔ dplyr 1.1.4 ✔ readr 2.1.5 ✔ forcats 1.0.0 ✔ stringr 1.5.1 ✔ ggplot2 3.5.2 ✔ tibble 3.2.1 ✔ lubridate 1.9.4 ✔ tidyr 1.3.1 ✔ purrr 1.0.4 ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ── ✖ dplyr::filter() masks stats::filter() ✖ dplyr::lag() Read More...

We will use core packages from the tidyverse for our data wrangling needs. Data reshaping primarily involves the tidyverse package, tidyr, but we will use additional packages as well, such as tibble. Packages must be Read More...

We do not need to load the dplyr package separately, as it is a core tidyverse package. If you need to install and load only dplyr, use install.packages("dplyr") and library(dplyr). Read More...

In this lesson, we are continuing with the package dplyr. We do not need to load the dplyr package separately, as it is a core tidyverse package. Again, if you need to install and load Read More...

The Antibody Characterization Laboratory (ACL) is the laboratory responsible for the development of well-characterized monoclonal antibody reagents. The NCI’s Office of Cancer Clinical Proteomics Research funds ACL as a resource to the entire cancer Read More...

Bruker AVANCE 400 and 500 MHz NMR instruments. Helium Cryoprobe technology on the 500 MHz machine for added sensitivity, especially for Carbon-13 spectra. Access to a second 500 MHz instrument with Prodigy Liquid Nitrogen-cooled cryoprobe. User Accounts can be Read More...

Electron Microscopy Laboratory (EML) The EML offers investigators access to unique expertise and EM technologies that allow our partners to explore new avenues of research to enhance the knowledge of biological systems. To assist our Read More...

The NIH MRI Research Facility (NMRF) is a shared, intramural resource for human imaging studies. The NMRF is supported by all Institutes at NIH and reports to the Shared Resources Subcommittee (SRS) of the Scientific Read More...

CREx Monthly Newsletter Learn about the NIH Collaborative Research Exchange (CREx), Core Facilities, Webinars, & More NIH Cores on CREx NIBIB BEPS Micro Analytical Immunochemistry Unit The Micro Analytical Immunochemistry Unit employs a variety Read More...

Back Services: This instrument is not user accessible.  We provide both data collection and data analysis services. Location: Building 50, room 3331 Description: An analytical ultracentrifuge is equipped with absorption and interference optical systems that monitor Read More...

The Mass Spectrometry Unit of the Collaborative Protein Technology Resource uses mass spectrometry for the study of proteins. We perform collaborative experiments with CCR researchers in areas such as: interactomes, quantitative global proteome analyses, and Read More...

The computational chemistry and protein modeling team in the Advanced Biomedical Computational Science (ABCS) group provides novel solutions in structural modeling and computational chemistry. Computational scientists in the group collaborate with NCI researchers by using Read More...

Notice that "sample" was treated as numeric, rather than as a character vector. If we intend to work with this column, we will need to convert it or coerce it to a character Read More...

ggplot2 is an R graphics package from the tidyverse collection. It allows the user to create informative plots quickly by using a 'grammar of graphics' implementation, which is described as "a coherent system for Read More...

To explore tidyverse functionality, let's read in some data and take a look. #let's use our differential expression results dexp "ENSG00000000003", "ENSG00000000419", "ENSG00000000457", "E… $ albut untrt, Read More...

Load in a tab delimited file (file_path= "./data/WebexSession_report.txt") using read_delim() . You will need to troubleshoot the error message and modify the function arguments as needed. {{Sdet}} Solution } library ( Read More...

Notice that "sample" was treated as numeric, rather than as a character vector. If we intend to work with this column, we will need to convert it or coerce it to a character Read More...

10/14/2022 - The call for better data and evidence for decision-making has become very real as evidenced by the Federal Data Strategy, as well as the passage of both the Foundations of  Evidence-based Policymaking Act (Evidence Read More...

06/04/2021 - Speaker: Rangan Sreenivas Sukumar Distinguished Technologist Hewlett Packard Enterprise (HPE) Abstract: In March of 2020, the “Force for Good” pledge of intellectual property to fight COVID-19 brought into action HPE products, resources and expertise to Read More...

04/12/2021 - Tumor heterogeneity and plasticity provide a driving force for tumor progression and metastasis as well as treatment response. Tumor heterogeneity can be explained by the same mechanisms that govern the developmental programs of an Read More...

Q4. Load in a tab delimited file (file_path= "./data/WebexSession_report.txt") using read_delim(). You will need to troubleshoot the error message and modify the function arguments as needed. Q4: Solution Read More...

Let's pretend that the sample IDs were numeric rather than of type character. smeta$SampleID <- c(1:nrow(smeta)) smeta SampleName cell dex albut Run avgLength Experiment Sample 1 GSM1275862 N61311 untrt untrt Read More...

Q1. Import data from the sheet "iris_data_long" from the excel workbook (file_path = "./data/iris_data.xlsx"). Make sure the column names are unique and do not contain spaces. Read More...

Sometimes you don't want git to track certain files (e.g. backup files created by your text editor, large data files, intermediate analysis files). This can be achieved using a special configuration file .gitignore Read More...

The function of the SAIP is to collaborate with NCI investigators in the development of mouse models, new molecular imaging probes for early detection and therapy, monitor tumors in vivo, and perform drug efficacy studies Read More...

Back Services: Biophysics Facility offers fluorometers as open-access instruments.  First-time users must complete a short training session before gaining access to the instrument reservation calendar. Location: Building 50, room 3226 Description: Some substances reemit light after Read More...

Services: Biophysics Facility offers CD as an open-access instrument.  First-time users must complete a short training session before gaining access to the instrument reservation calendar. Location: Building 50, room 3123 Description: CD spectroscopy measures the difference Read More...

Back Services: Biophysics Facility offers CD as an open-access instrument.  First-time users must complete a short training session before gaining access to the instrument reservation calendar. Location: Building 50, room 3123 Description: CD spectroscopy measures the Read More...

Home About the Biophysics Core Biophysics Core Services [tabby title="Instrumentation"] NHLBI Biophysics Core The Biophysics Core Facility: Overview Core Facilities provide scientific resources, cutting-edge technologies and novel approaches to support DIR scientists. Availability of Read More...

Objectives Review the grammar of graphics template. Learn about the statistical transformations inherent to geoms. Learn more about fine tuning figures with labels, legends, scales, and themes. Learn how to save plots with ggsave() . Review Read More...

In this lesson, attendees will learn how to transform, summarize, and reshape data using functions from the tidyverse. Learning Objectives Continue to wrangle data using tidyverse functionality. To this end, you should understand: how to Read More...

Data visualization with ggplot2 Objectives To learn how to create publishable figures using the ggplot2 package in R. By the end of this lesson, learners should be able to create simple, pretty, and effective figures. Read More...

In this lesson, attendees will learn how to transform, summarize, and reshape data using functions from the tidyverse. Learning Objectives Continue to wrangle data using tidyverse functionality. To this end, you should understand: how to Read More...

Learning Objectives Learn about data structures including factors, lists, data frames, and matrices. Load, explore, and access data in a tabular format (data frames) Learn to write out (export) data from the R environment Data Read More...

This lesson will introduce data wrangling with R. Attendees will learn to filter data using base R and tidyverse (dplyr) functionality. Learning Objectives Understand the concept of tidy data. Become familiar with the tidyverse packages. Read More...

All solutions should use the pipe. Import the file "./data/filtlowabund_scaledcounts_airways.txt" and save to an object named sc . Create a subset data frame from sc that only includes the columns Read More...

Help Session Lesson 5 All solutions should use the pipe. Import the file "./data/filtlowabund_scaledcounts_airways.txt" and save to an object named sc . Create a subset data frame from sc that only Read More...

Help Session Lesson 3 Loading data Import data from the sheet "iris_data_long" from the excel workbook (file_path = "./data/iris_data.xlsx"). Make sure the column names are unique and Read More...

dplyr : joining, tranforming, and summarizing data frames Objectives Today we will continue to wrangle data using the tidyverse package, dplyr . We will learn: how to join data frames using dplyr how to transform and create Read More...

Introduction to dplyr and the %>% Objectives Today we will begin to wrangle data using the tidyverse package, dplyr . To this end, you will learn: how to filter data frames using dplyr how to employ Read More...

Data import and reshape Objectives 1. Learn to import multiple data types 2. Data reshape with tidyr : pivot_longer() , pivot_wider() , separate() , and unite() Installing and loading packages So far we have only worked with objects that Read More...

Tidy data implies that we have one observation per row and one variable per column. This generally means data is in a long format. However, whether data is tidy or not will depend on what Read More...

Data frames Objectives To be able to load, explore, and access data in a tabular format. To this end, students should understand the following: 1. how to import and export data 2. how to create, summarize, and Read More...

Introduction to Data Wrangling with the Tidyverse Objectives Wrangle data using tidyverse functionality (i.e., dplyr ). To this end, you should understand: 1. how to use common dplyr functions (e.g., select() , group_by() , arrange() , mutate() , Read More...

05/22/2017 - Driven by the decreasing costs and increasing performance of next-generation sequencing (NGS) technologies, the amount of available genomic data has grown exponentially in recent years.  While most of the analyses of these data is Read More...

We will continue with penguins for this exercise. Questions and solutions (Q1-Q3) were taken from https://allisonhorst.shinyapps.io/dplyr-learnr/#section-dplyrgroup_by-summarize. First, let's convert penguins to a tibble. penguins <- Read More...

All solutions use the pipe. Solutions have multiple possibilities. Q1. Import the file "./data/filtlowabund_scaledcounts_airways.txt" and save to an object named sc. Create a data frame from sc that only Read More...