Despite increasingly strict journal policies requiring the release of computational code files along with research papers, many scientists remain reluctant to share—underscoring the need for better solutions.
Brianna Chrisman and Jordan Eizenga | Sep 1, 2022 | 10+ min read
Thirty years out from the start of the Human Genome Project, researchers have finally finished sequencing the full 3 billion bases of a person’s genetic code. But even a complete reference genome has its shortcomings.
Armed with improved imaging techniques and supercomputers, researchers are generating detailed three-dimensional images of cellular structures that anyone can explore.
Karen Miga discusses how she and collaborators sequenced the missing parts of the human genome almost two decades after the first Human Genome Project published its results.
More than 3,000 researchers have signed on to a petition that expresses concern over the agency’s 2021 application for the funding program, which emphasizes three areas of computational science and might further disadvantage underrepresented groups.
Researchers’ simulations suggest that small population sizes and inbreeding made Neanderthal populations vulnerable to chance fluctuations in population size.
Machine learning can analyze photographs of cancer, tumor pathology slides, and genomes. Now, scientists are poised to integrate that information into cancer uber-models.
The Carnegie Mellon computational biologist thinks machine learning algorithms can direct high-throughput experiments to solve the field’s unanswered questions.
