COLUMN: Letter from the Editors
Code of Life: Unraveling Biological Mysteries through Computational Innovation
By Jiayi Li
By Jiayi Li
By Meng Wang, Xinzhou Ge
By Gopal Mengi
By Eric J. Gonzalez
When Los Angeles is mentioned, cycling is usually not the first thing that comes to mind. However, during my past 10 years in LA studying molecular biology and bioinformatics, my bike trips through the geographical space of LA have inspired many ideas in my research in spatial data analysis in bioinformatics. I have written software to bring decades of research in geospatial data analysis to spatial -omics, as my trips make me ponder on spatial phenomena in general.
By Lambda Moses
Protein language models were nurtured by unlikely parents---corporations. Now that they have come of age, they have been forced to strike out on their own. A common pitfall that biotechnology platforms make is to attempt to solve as many problems, all at once, while in reality solving none. Whether these fledgling protein LLM companies will learn from the mistakes of their industry predecessors remains to be seen.
By Albin Hartwig
Reconstructing the network of life from molecular data is a complicated task. How can computational algebraic geometry play a role?
By Elizabeth Gross, John Rhodes
Researchers are developing new statistical and machine learning methods to effectively integrate biobank-scale whole-genome sequencing multi-omics and electronic health records data to better understand the molecular basis of complex human diseases.
By Xihao Li
When you use the most popular computational methods for biological data analysis, have you checked whether their models are reasonable in your settings?
By Xinzhou Ge
By Zhongxuan He