The RCS Spring 2018 tutorial schedule will be posted here when it is ready in early January.

Fall 2017 Tutorial Series

September 6, 2017 – October 5, 2017

The Research Computing Services (RCS) group, part of Boston University Information Services & Technology, will offer a series of tutorials on programming, high performance computing, and scientific visualization. These tutorials are free and open to all members of the Boston University community.

In addition to covering concepts, techniques, and tools which researchers may use in their own computing environments, these tutorials are designed to help you make effective use of the Boston University Shared Computing Cluster. We can also deliver extra, or customized, tutorial sessions to your group or lab. Please contact us at rcs@bu.edu if you are interested.

There are four brand new tutorials this Fall in addition to our usual offerings. These are Introduction to High-Performance Computing, Managing Projects on the SCC, Python for Data Analysis, and Introduction to ImageJ.

Register

Charles River Campus Tutorials


Register

BU Medical Campus (BUMC) Tutorials

You may register for as many tutorials as you like. Registration is required and is accessed with your BU Kerberos password.

If you don’t have a Kerberos password, or if you find that a tutorial is full, or have any other questions, please send email to rcs-tutorial@bu.edu.

Tutorial Locations and Directions

Charles River Campus (CRC)

All CRC sessions will be held in MCS B27 at 111 Cummington Mall (with one exception: Introduction to Maya will be held at the CAS Computer Lab, 685 Commonwealth Avenue, room 327.) To access MCS B27, we recommend that you enter 111 Cummington Mall via the “College of Arts & Sciences – Department of Computer Science – Department of Mathematics & Statistics” entrance, and then either: take the elevator immediately on your right; or descend the stairs down the hall to your right.

BU Medical Campus (BUMC)

The BUMC sessions will be held in the “L” building at 72 E Concord St using room number L1110. The “L” building is the BUMC main instructional building and the 11th floor is accessible by elevator. The tutorial room is at the end of the hall on the left.


Tutorial Descriptions and Times

Research Computing Basics Tutorials

Introduction to Linux (Hands‐on)

Instructor: Charlie Jahnke (cjahnke@bu.edu)

Thursday, September 7, 10:00am – 12:00pm
Friday, September 8, 1:15pm – 3:15pm
Tuesday, September 19, 10:00am – 12:00pm, BUMC L1110

This tutorial will give attendees a hands-on introduction to Linux. Topics covered will include a short history of Linux, logging in with ssh, the Bash shell and shell scripts, I/O redirection (pipes), file system navigation, and job control. Time permitting, attendees will edit, compile, and run a simple C program.

Introduction to BU’s Shared Computing Cluster (Hands‐on)

Instructor for CRC: Aaron Fuegi (aarondf@bu.edu)

Instructor for BUMC: Charlie Jahnke (cjahnke@bu.edu)

Thursday, September 7, 1:15pm – 3:15pm
Friday, September 8, 10:00am – 12:00pm
Monday, September 18, 10:00am – 12:00pm, BUMC L1110

This tutorial will introduce Boston University’s Shared Computing Cluster (SCC) in Holyoke, MA. This Linux cluster has more than 6000 processors and over two petabytes of storage available for Research Computing by students and faculty on the Charles River and BUMC campuses. A very large number of software packages for programming, mathematics, data analysis, plotting, statistics, visualization, and domain-specific disciplines are available as well on the SCC. You will get a general overview of the SCC and the facility that houses it and then a hands-on introduction covering connecting to and using the SCC for new users. This tutorial will cover a few basic Linux commands but we strongly encourage people to also take our more extensive “Introduction to Linux” tutorial.

There will also be ample time for questions of all types about the SCC. Those who wish can bring their own laptops and we will help you with installing the software you need to effectively connect to and use the SCC. Others will use the Windows machines in the room.

Intermediate Usage of the SCC

Instructor for CRC: Katia Oleinik (koleinik@bu.edu)

Instructor for BUMC: Charlie Jahnke (cjahnke@bu.edu)

Monday, September 11, 1:15pm – 3:15pm
Thursday, September 21, 10:00am – 12:00am, BUMC L1110

This tutorial will provide some more advanced techniques and common strategies used for interacting with the Shared Computing Cluster and its resources.

The topics discussed during the tutorial include:

  • Customizing your environment
  • Parallel computing on the SCC
  • Jobs monitoring (CPU and memory usage)
  • Profiling programs for performance optimization
  • General optimization strategies

Recommended prerequisite: some prior experience with high performance computing or attendance of our “Introduction to BU’s Shared Computing Cluster” tutorial.

Managing Projects on the SCC for LPIs

Instructor: Charlie Jahnke (cjahnke@bu.edu)

Tuesday, September 26, 10:00am – 12:00am, BUMC L1110
Wednesday, September 27, 1:15pm – 3:15pm

Intended for Lead Project Investigators (LPI) and Administrative Contacts, this tutorial covers a high level overview and best practices for managing projects on the Shared Computing Cluster (SCC). Topics include compute resources, project creation, project management, storage/SU allocation management, and the Buy-In Program.

Register

Computer Programming Tutorials

Introduction to C Programming, Part One (Hands‐on)

Instructor: Brian Gregor (bgregor@bu.edu)

Tuesday, September 12, 10:00am – 12:00pm

This tutorial is primarily aimed at those who have some experience programming in another language, such as MATLAB, and want to learn to read, write, and modify C codes in a Unix environment. Although previous programming experience would be helpful, it is not mandatory. In this tutorial we will cover basic syntax, and write, compile, and run some simple codes. Basics of makefiles will also be covered. Please remember to sign up for all four sessions to complete the tutorial.

Introduction to C Programming, Part Two (Hands‐on)

Instructor: Brian Gregor (bgregor@bu.edu)

Wednesday, September 13, 10:00am – 12:00pm

This tutorial is a continuation of Introduction to C Programming, Part One (Hands‐on) described above. We strongly recommend that if you are interested in this tutorial, you also register for Parts One, Three, and Four.

Introduction to C Programming, Part Three (Hands‐on)

Instructor: Brian Gregor (bgregor@bu.edu)

Thursday, September 14, 10:00am – 12:00pm

This tutorial is a continuation of Introduction to C Programming, Part Two (Hands‐on) described above. We strongly recommend that if you are interested in this tutorial, you also register for Parts One, Two, and Four.

Introduction to C Programming, Part Four (Hands‐on)

Instructor: Brian Gregor (bgregor@bu.edu)

Friday, September 15, 10:00am – 12:00pm

This tutorial is a continuation of Introduction to C Programming, Part Three (Hands‐on) described above. We strongly recommend that if you are interested in this tutorial, you also register for Parts One, Two, and Three.

Introduction to Python for Non-programmers, Part One (Hands‐on)

Instructor: Brian Gregor (bgregor@bu.edu)

Tuesday, September 12, 1:15pm – 3:15pm

Prerequisite: zero programming experience. We will go slowly so that everyone understands programming concepts, like loops and functions.

This is an introduction to the essential features of Python. This tutorial includes a brief introduction to basic types (Integer, Float, String, and Boolean), if-statements, functions, lists, dictionaries, loops, and modules. We’ll look at some simple interactive tasks. After this tutorial you’ll be ready to explore all the amazing modules Python has to offer.

This is a two part tutorial, so please sign up for both parts.

Introduction to Python for Non-programmers, Part Two (Hands‐on)

Instructor: Brian Gregor (bgregor@bu.edu)

Thursday, September 14, 1:15pm – 3:15pm

This tutorial is a continuation of Introduction to Python for Non-programmers, Part One. Please make sure to sign up for that session as well. We will complete the introduction to programming and the Python language.

Introduction to Perl, Part One

Instructor: Tim Kohl (tkohl@bu.edu)

Friday, September 15, 1:15pm – 3:15pm

Perl is a powerful and versatile programming language that can be used for a wide variety of programming tasks, including, but not limited to, text/data processing, system administration, and Web applications. Combing elements of C, Unix shell scripting languages, as well as text-processing utilities such as sed and awk, Perl can be used for both large scale projects and for small applications. Some experience in a command line environment (e.g. Unix) is helpful, but the basics of Perl are simpler than those of other languages making it accessible to a new programmer. Attending our Introduction to Linux tutorial or equivalent background is recommended. Please remember to sign up for all four sessions to complete the tutorial.

Introduction to Perl, Part Two

Instructor: Tim Kohl (tkohl@bu.edu)

Monday, September 18, 1:15pm – 3:15pm

This tutorial is a continuation of Introduction to Perl, Part One. We strongly recommend that if you are interested in this tutorial, you register for Parts One, Three, and Four as well.

Introduction to Perl, Part Three

Instructor: Tim Kohl (tkohl@bu.edu)

Wednesday, September 20, 1:15pm – 3:15pm

This tutorial is a continuation of Introduction to Perl, Part Two. We strongly recommend that if you are interested in this tutorial, you register for Parts One, Two, and Four as well.

Introduction to Perl, Part Four

Instructor: Tim Kohl (tkohl@bu.edu)

Friday, September 22, 1:15pm – 3:15pm

This tutorial is a continuation of Introduction to Perl, Part Three. We strongly recommend that if you are interested in this tutorial, you register for Parts One, Two, and Three as well.

Version Control and Collaboration with Git and GitHub (Hands-on)

Instructor: Katia Oleinik (koleinik@bu.edu)

Monday, September 18, 3:30pm – 5:30pm
Monday, September 25, 10:00am – 12:00pm, BUMC L1110

Whether you are writing source code or a manuscript, keeping track of changes is a critial part of a successful project. Version control software, like Git, automates the process of backing up and annotating previous versions of your evolving projects. In conjunction with online hosting services like GitHub, it also greatly simplifies the logistical difficulties of working in parallel with collaborators. This “hands-on” tutorial will cover basic usage of the popular version control software Git and the online hosting service GitHub.

Basic knowledge of a the Linux command line is assumed.

Introduction to Python (Hands‐on)

Instructor: Brian Gregor (bgregor@bu.edu)

Tuesday, September 19, 6:00pm – 8:00pm
Thursday, September 21, 3:30pm – 5:30pm
Wednesday, September 27, 10:00am – 12:00pm, BUMC L1110

Prerequisite: some programming experience. For example, you should understand concepts like loops or functions.

This is a basic introduction to the essential features of Python. This tutorial includes a brief introduction to basic types (Integer, Float, String, and Boolean), if-statements, functions, lists, dictionaries, loops, and modules. We’ll look at some simple interactive tasks. After this tutorial you’ll be ready to explore all the amazing modules Python has to offer.

Learning Perl through Examples, Part One (Hands-on)

Instructor: Yun Shen (yshen16@bu.edu)

Thursday, September 21, 2:00pm – 4:00pm, BUMC L1110

This Perl tutorial, offered on the BU Medical Campus, is designed with some possible bioinformatical applications of the language in mind. It is oriented towards those who have little or no prior programming experience and would like to get a solid start. It will introduce Perl through an integrated approach, covering all of the fundamentals of the Perl language, from code design and implementation to debugging and execution. It will also include information on the Perl help system, to ease the learning curve and provide an entry point for continuous exploration of the language. The tutorial itself will focus mostly on methodology and concepts; however, it will make an effort to achieve this goal through several quite simple, yet representative, code examples.

The entire tutorial will be divided into two sessions. The first session will give students a brief overview and general information about Perl, with some hands-on exercises. The second session will focus on some frequently used language features, such as file I/O, string processing, regular expressions, and even some more advanced features, such as code reuse. All of the features will be introduced through some real bioinformatical examples. Please remember to sign up for both sessions to complete the tutorial.

Learning Perl through Examples, Part Two (Hands-on)

Instructor: Yun Shen (yshen16@bu.edu)

Friday, September 22, 2:00pm – 4:00pm, BUMC L1110

This tutorial is a continuation of Learning Perl through Examples, Part One. Please make sure to sign up for that first part as well. We will focus here on some frequently used Perl features.

Introduction to C++ Programming, Part One (Hands‐on)

Instructor: Brian Gregor (bgregor@bu.edu)

Monday, September 25, 10:00am – 12:00pm

This tutorial is aimed at those who want to learn to read, write, and modify C++ code. Previous programming experience in languages such as C, MATLAB, or Python is recommended but it is not mandatory. In this tutorial series we will cover basic C++ syntax, object-oriented programming concepts including classes and inheritance, and parts of the C++ standard library. This is a hands-on tutorial and we will write, compile, and run some simple codes using the Code::Blocks integrated development environment. Please remember to sign up for all four sessions to complete the tutorial.

Introduction to C++ Programming, Part Two (Hands‐on)

Instructor: Brian Gregor (bgregor@bu.edu)

Tuesday, September 26, 10:00am – 12:00pm

This tutorial is a continuation of Introduction to C++ Programming, Part One. We strongly recommend that if you are interested in this tutorial, you also register for Parts One, Three, and Four.

Introduction to C++ Programming, Part Three (Hands‐on)

Instructor: Brian Gregor (bgregor@bu.edu)

Thursday, September 28, 10:00am – 12:00pm

This tutorial is a continuation of Introduction to C++ Programming, Part Two. We strongly recommend that if you are interested in this tutorial, you also register for Parts One, Two, and Four.

Introduction to C++ Programming, Part Four (Hands‐on)

Instructor: Brian Gregor (bgregor@bu.edu)

Friday, September 29, 10:00am – 12:00pm

This tutorial is a continuation of Introduction to C++ Programming, Part Three. We strongly recommend that if you are interested in this tutorial, you also register for Parts One, Two, and Three.

Building Software from Source Code on Linux (Hands‐on)

Instructor: Shaohao Chen (shaohao@bu.edu)

Monday, October 2, 10:00am – 12:00pm

Compiling a working executable from C or Fortran source code can be a frustrating experience for new programmers. This “hands-on” tutorial will introduce the basic steps for compiling small- to medium-sized projects. Topics include working with multiple source files, header files, and external libraries, and automation using Make and Autotools (configure). For simplicity, we will only cover the build process for systems with a Linux operating system (such as the BU Shared Computing Cluster).

Familiarity with the Linux command line is assumed. Familiarity with C or Fortran will be helpful, but is not required.

Register

Data Analysis Tutorials

Introduction to R (Hands‐on)

Instructor: Katia Oleinik (koleinik@bu.edu)

Monday, September 11, 3:30pm – 5:30pm
Monday, September 18, 10:00am – 12:00pm
Monday, September 25, 2:00pm – 4:00pm, BUMC L1110

R is the most powerful, rapidly developing, highly reliable, open source statistical language. It is widely used among statisticians for the development of statistical software and for data analysis. New features appear every few months.

This tutorial introduces the R environment for statistical computing and will cover the following topics:
  • operators and arithmetic operations
  • atomic types, variable rules and built-in constants
  • scalar and vector function overview
  • working with data (workspace setup as well as reading, creating, exploring, and saving data)
  • working with R data types (vectors, matrices, lists, data frames)
  • working with script files
  • installing and loading R extension packages and getting help
  • overview of functions for data analysis
After completing this tutorial you will:
  • know the basics of the R environment.
  • get a solid understanding of various data types and objects used in R.
  • be able to create, load and analyze data.
  • find appropriate functions and get necessary help and examples for these functions.

Graphics in R (Hands‐on)

Instructor: Katia Oleinik (koleinik@bu.edu)

Tuesday, September 12, 3:30pm – 5:30pm
Tuesday, September 19, 10:00am – 12:00pm
Tuesday, September 26, 2:00pm – 4:00pm, BUMC L1110

R provides extensive and powerful graphics options that allow for the production of publication-ready, high quality diagrams, and plots. This tutorial introduces R graphics libraries and functions.

After completing this tutorial you will:
  • understand what to expect from R’s graphics capabilities.
  • be able to create, modify, and customize graphs and plots used in statistical analysis.
  • find appropriate libraries, download, and use them for your visualization needs.

Prerequisite: If you are new to the R environment we strongly recommend that you also register for the “Introduction to R” tutorial.

Programming in R (Hands‐on)

Instructor: Katia Oleinik (koleinik@bu.edu)

Thursday, September 14, 3:30pm – 5:30pm
Thursday, September 21, 10:00am – 12:00pm
Thursday, September 28, 2:00pm – 4:00pm, BUMC L1110

This tutorial is the third in a series of R tutorials. It introduces basic R programming, debugging and optimization techniques and develops practices of proper and efficient R coding. It covers the following topics:

  • if-else and switch statements
  • types of loops (for, while, repeat) and loop control statements (next, break)
  • user functions and argument definitions
  • local and global variables
  • apply function family
  • sourcing, timing, compilation and debugging
  • code profiling and optimization

Prerequisite: We strongly recommend that you also register for the “Introduction to R” tutorial if you are new to the R environment.

R Code Optimization

Instructor: Katia Oleinik (koleinik@bu.edu)

Friday, September 22, 10:00am – 12:00pm
Friday, September 29, 2:00pm – 4:00pm, BUMC L1110

This tutorial is primarily aimed at those who have some experience working in a Linux environment and programming in R. The topics covered in this tutorial:

  • debugging and profiling R code
  • choosing the right functions to speed-up your code
  • parallelization techniques
  • tuning your code for faster performance on the SCC cluster

Introduction to MATLAB (Hands‐on)

Instructor: Shaohao Chen (shaohao@bu.edu)

Wednesday, September 20, 3:30pm – 5:30pm
Thursday, September 21, 1:15pm – 3:15pm

MATLAB (MATrix LABoratory) is a numerical computing environment developed by MathWorks, Inc. In short, MATLAB is a highly optimized interpreted programming language designed for intuitive and fast development of scientific computing software. This “hands-on” tutorial will introduce the MATLAB programming environment and the basic tools you will need to write your own MATLAB programs. Topics include matrix variables and operations, reading/writing data, plotting, loops, conditional statements, scripts, and functions.

No prior programming experience in any language is required to attend this course.

Python for Data Analysis (Hands‐on)

Instructor: Katia Oleinik (koleinik@bu.edu)

Friday, September 15, 3:30pm – 5:30pm
Friday, September 22, 3:30pm – 5:30pm
Thursday, September 28, 10:00am – 12:00pm, BUMC L1110

This tutorial will introduce the basics of Data Analysis with Python and its powerful libraries such as Pandas and Matplotlib.

What you will learn:
  • Importing and Exporting the data
  • Basic data processing, cleaning, and manipulation
  • Basic inferential statistical analysis
  • Data Visualization techniques

Prerequisite: basic familiarity with the Python environment or one of our Introduction to Python tutorials.

Introduction to SAS (Hands‐on)

Instructor: Jack Chan (jack@bu.edu)

Monday, October 2, 1:15pm – 2:15pm
Tuesday, October 3, 1:15pm – 2:15pm

SAS (Statistical Analysis System) is one of the most powerful statistical packages available on any computer platform. This tutorial will introduce you to SAS on the desktop.

After completing this tutorial, you will be able to:
  • access SAS on Windows
  • create, edit, and save program files containing SAS commands
  • obtain printed output
  • create, run, and modify your own programs

Introduction to SPSS (Hands‐on)

Instructor: Jack Chan (jack@bu.edu)

Monday, October 2, 2:15pm – 3:15pm
Tuesday, October 3, 2:15pm – 3:15pm

SPSS (Statistical Package for the Social Sciences) is a widely used program for analyzing data. SPSS uses windows and dialog boxes to manipulate data and perform statistical analyses. This hands-on tutorial will introduce you to the basics of SPSS and will give you one hours’ practice using SPSS on Microsoft Windows.

After completing this tutorial, you will be able to:
  • enter data into SPSS
  • use SPSS to transform data
  • use SPSS to perform basic statistical analyses

Register

High Performance Computing Tutorials

Introduction to High-Performance Computing

Instructor: Shaohao Chen (shaohao@bu.edu)

Wednesday, September 6, 1:15pm – 2:15pm

High-performance computing (HPC) or supercomputing (SC) refers to the practice of aggregating computing power in order to solve large problems in science, engineering, or business. In this tutorial, the following questions will be discussed: Why a computer cluster is necessary? What is the basic structure of a computer cluster? What resources does an HPC system provide? How to measure computer performance? What are the most powerful computers in the world? What scientific disciplines benefit from HPC? What is parallel computing? In particular, the nation-wide HPC resource XSEDE (eXtreme Science and Engineering Discovery Environment) will be introduced. This tutorial will also guide you to other RCS tutorials being offered this semester that might be helpful to your particular study or research work.

MATLAB for High-Performance Computing (Hands-on)

Instructor: Shaohao Chen (shaohao@bu.edu)

Monday, September 25, 1:15pm – 3:15pm

MATLAB programs can be exceptionally fast if they are well-designed, and painfully slow if not. Fortunately, it does not take a professional programmer to write an efficient MATLAB program or to take advantage of multi-core processors and computer clusters. This tutorial will introduce (1) using MATLAB on the BU SCC, and (2) optimizing MATLAB codes. The first part will cover how to use the MATLAB platform remotely and how submitting batch jobs for MATLAB works. In the second part, some useful skills for removing unnecessary computation and optimizing memory usage will be introduced. The skills you learn should enable you to solve bigger problems faster using MATLAB.

Introduction to OpenMP

Instructor: Shaohao Chen (shaohao@bu.edu)

Monday, September 25, 3:30pm – 5:30pm

The OpenMP application program interface (API) provides simple and flexible tools to develop parallel software for shared-memory multiprocessor systems. The basic approach to parallelizing with OpenMP is to insert special comments (directives) into the code that assist the compiler in mapping computation onto the CPUs. The beauty of this approach is that it is often possible to create efficient parallel code with only minor modifications to a serial code. This tutorial covers the major features of OpenMP through discussion and examples in C and Fortran.

Some experience in C or Fortran programming is assumed. Understanding of parallel programming in general is helpful, but not required.

Introduction to MPI, Part One (Hands-on)

Instructor: Shaohao Chen (shaohao@bu.edu)

Tuesday, September 26, 1:15pm – 3:15pm

On contemporary computers, speeding up computations is most often achieved by employing multiprocessors concurrently on shared.memory multi.cored nodes or multiprocessor distributed.memory clusters. MPI is a library of communication functions to enable and enhance multiprocessing on these computer architectures. This tutorial introduces many of the basic MPI functions through practical examples. Working knowledge of C or Fortran is required to attend the course. Basic knowledge of Unix/Linux will be helpful.

Introduction to MPI, Part Two (Hands-on)

Instructor: Shaohao Chen (shaohao@bu.edu)

Thursday, September 28, 1:15pm – 3:15pm

This tutorial is a continuation of Introduction to MPI, Part One. We recommend that, if you are interested in this tutorial, you also register for Part One.

Introduction to GPU Programming

Instructor: Brian Gregor (bgregor@bu.edu)

Tuesday, September 26, 3:30pm – 5:30pm

Originally designed to render computer graphics, GPUs now provide the ability to accelerate scientific applications traditionally handled by CPUs. This tutorial is an introduction to general programming using GPUs. We will explore the applications that would benefit the most from GPU acceleration, go over different languages and software tools available on our Linux cluster, and discuss their benefits for different types of applications.

Introduction to CUDA (Hands-on)

Instructor: Brian Gregor (bgregor@bu.edu)

Wednesday, September 27, 3:30pm – 5:30pm

This tutorial will show you how to do calculations with CUDA C/C++, an API for programming massively parallel GPUs.

In this tutorial you will learn to do the following tasks in CUDA:

  • Write a basic “Hello, World!” program
  • Write and launch CUDA C kernels
  • Manage GPU memory
  • Run parallel kernels in CUDA C
  • Parallel communication and synchronization
  • Race conditions and atomic operations

C/C++ programming experience is required for this tutorial. You do not need prior parallel programming or graphics experience.

MATLAB Parallel Computing Toolbox (Hands‐on)

Instructor: Shaohao Chen (shaohao@bu.edu)

Friday, September 29, 1:15pm – 3:15pm

The MATLAB Parallel Computing Toolbox allows you to write programs that leverage multi-core processors, GPUs, and computer clusters by dividing up work between independent cores. Converting serial MATLAB applications to parallel MATLAB applications usually requires few code modifications and no programming in a low-level language. This tutorial will introduce MATLAB parallel processing tools, such as parfor, spmd, and distributed array types. The skills you learn should enable you to solve bigger problems faster using MATLAB.

Basic knowledge of MATLAB is assumed.

Register

Visualization Tutorials

Introduction to Maya (Hands‐on)

Instructor: Laura Giannitrapani (laura@bu.edu)

Thursday, September 21 3:30pm – 6:30pm

Autodesk Maya 2017 is a powerful state-of-the-art 3D modeling and animation software package. It has a wide variety of modeling, animation, special effects, and rendering tools. It has a customizable graphical user interface as well as a scripting language for optimal flexibility in problem solving and production.

In this tutorial we will show you how to get started using Maya. We will teach you the basic workflow for modeling, creating and applying materials, animation, and rendering. We will also cover the basics of importing scientific geometric data and creating high quality renderings and animations from it.

Ordinarily Maya is considered to have a steep learning curve, but in this tutorial we will present a workflow which will provide a sound foundation for pursuing more complex projects.

Note the different location for this tutorial. It will be held at the CAS Computer Lab, 685 Commonwealth Avenue, Room 327.

Introduction to ImageJ (Hands‐on)

Instructor: Brian Gregor (bgregor@bu.edu)

Tuesday, October 3, 10:00am – 12:00pm
Thursday, October 5, 10:00am – 12:00pm

ImageJ is a popular open source tool for image analysis and processing. In this tutorial we will cover the use of ImageJ for basic image manipulation, writing ImageJ macros, and quantitative measurements of a fluorescent image. The details of different image file formats and using ImageJ in preparing and formatting images for publication will also be covered.

Register