iBiology Podcast

Daniel Colón-Ramos began his life in science by being fascinated as a young boy by the unique environment of his native Puerto Rico. But in formal schooling, he found the excitement of discovery too often absent. Now a respected researcher at Yale University, Dr. Colón-Ramos keeps his boyhood enthusiasm for the awe and wonder of the natural world. He is eager to encourage scientific exploration and share his infectious spirit with his students and the larger world, as he does in this inspiring conversation with Dan Rather.

Jennifer Doudna tells the story of how studying the way bacteria fight viral infection turned into a genomic engineering technology that has transformed molecular biology research. In 2013, Doudna and her colleagues developed the CRISPR-Cas9 gene expression system that, when introduced into animal cells, makes site-specific changes to intact genomes. CRISPR-Cas9 is more precise, more efficient, and less expensive than other genome editing tools and, as a result, has facilitated a wide range of studies that were previously unachievable.

Since 1987, different versions of ImageJ have been used by scientists to analyze biological images. In this talk, Dr. Kevin Eliceiri provides an overview of ImageJ, explains how ImageJ has evolved through time, and demonstrates major functionalities of this open-source software.

The Scientific Community Image Forum is an online resource that helps scientists answer their bioimage analysis questions. In this talk, Dr. Anne Carpenter and Dr. Kevin Eliceiri encourage scientists to use the Scientific Community Image Forum when they have image analysis difficulties, and to familiarize themselves with the different tools that they can use to answer their questions.

In this series, Dr. Anne Carpenter and Dr. Kevin Eliceiri provide an overview of bioimage analysis. Pre-processing is the first step that follows image acquisition and will prepare your image by reducing the signal-to-noise ratio, applying appropriate filters to the image, and color extraction. Once you perform pre-processing, you’re ready for segmentation, the process of identifying individual cells or structures within an image. If appropriate for your dataset, you can use tracking to be able to link objects in space and time and measure speed, directionality, and cell division. The last step of bioimage analysis is to analyze the data by measuring different features like the number of cells or biological structures, or their size, shape, intensity or texture. Carpenter and Eliceiri finalize this series by providing tips on best practices that will aid scientists in properly analyzing their data.

In this series, Dr. Anne Carpenter and Dr. Kevin Eliceiri provide an overview of bioimage analysis. Pre-processing is the first step that follows image acquisition and will prepare your image by reducing the signal-to-noise ratio, applying appropriate filters to the image, and color extraction. Once you perform pre-processing, you’re ready for segmentation, the process of identifying individual cells or structures within an image. If appropriate for your dataset, you can use tracking to be able to link objects in space and time and measure speed, directionality, and cell division. The last step of bioimage analysis is to analyze the data by measuring different features like the number of cells or biological structures, or their size, shape, intensity or texture. Carpenter and Eliceiri finalize this series by providing tips on best practices that will aid scientists in properly analyzing their data.

In this series, Dr. Anne Carpenter and Dr. Kevin Eliceiri provide an overview of bioimage analysis. Pre-processing is the first step that follows image acquisition and will prepare your image by reducing the signal-to-noise ratio, applying appropriate filters to the image, and color extraction. Once you perform pre-processing, you’re ready for segmentation, the process of identifying individual cells or structures within an image. If appropriate for your dataset, you can use tracking to be able to link objects in space and time and measure speed, directionality, and cell division. The last step of bioimage analysis is to analyze the data by measuring different features like the number of cells or biological structures, or their size, shape, intensity or texture. Carpenter and Eliceiri finalize this series by providing tips on best practices that will aid scientists in properly analyzing their data.

In this series, Dr. Anne Carpenter and Dr. Kevin Eliceiri provide an overview of bioimage analysis. Pre-processing is the first step that follows image acquisition and will prepare your image by reducing the signal-to-noise ratio, applying appropriate filters to the image, and color extraction. Once you perform pre-processing, you’re ready for segmentation, the process of identifying individual cells or structures within an image. If appropriate for your dataset, you can use tracking to be able to link objects in space and time and measure speed, directionality, and cell division. The last step of bioimage analysis is to analyze the data by measuring different features like the number of cells or biological structures, or their size, shape, intensity or texture. Carpenter and Eliceiri finalize this series by providing tips on best practices that will aid scientists in properly analyzing their data.

In this series, Dr. Anne Carpenter and Dr. Kevin Eliceiri provide an overview of bioimage analysis. Pre-processing is the first step that follows image acquisition and will prepare your image by reducing the signal-to-noise ratio, applying appropriate filters to the image, and color extraction. Once you perform pre-processing, you’re ready for segmentation, the process of identifying individual cells or structures within an image. If appropriate for your dataset, you can use tracking to be able to link objects in space and time and measure speed, directionality, and cell division. The last step of bioimage analysis is to analyze the data by measuring different features like the number of cells or biological structures, or their size, shape, intensity or texture. Carpenter and Eliceiri finalize this series by providing tips on best practices that will aid scientists in properly analyzing their data.

In this series, Dr. Anne Carpenter and Dr. Kevin Eliceiri provide an overview of bioimage analysis. Pre-processing is the first step that follows image acquisition and will prepare your image by reducing the signal-to-noise ratio, applying appropriate filters to the image, and color extraction. Once you perform pre-processing, you’re ready for segmentation, the process of identifying individual cells or structures within an image. If appropriate for your dataset, you can use tracking to be able to link objects in space and time and measure speed, directionality, and cell division. The last step of bioimage analysis is to analyze the data by measuring different features like the number of cells or biological structures, or their size, shape, intensity or texture. Carpenter and Eliceiri finalize this series by providing tips on best practices that will aid scientists in properly analyzing their data.