Here are my 12 guidelines for data exploration and analysis with the right attitude for discovery:
1. You never really finish analyzing a dataset. You just decide to stop and move on at some point, leaving some things undiscovered. 🧵
Researchers from @umeauniversity, in collaboration with international colleagues, established G-protein coupled receptors and neuropeptide mutant libraries of C. elegans using CRISPR/Cas9-based approaches. A powerful resource for screening, now published in @NatureComms.
Seeking #postdocjobs - we want you! The IceLab #multidisciplinary postdoctoral fellowships are accepting applications now. You should have math & #computational modeling skills & a deep interest in working with empirical researchers. Welcome to IceLab! https://t.co/sTupurhLSR
@strategiskaSSF Swedish funders has to create options to hire prospect PhD students from UA. It would be an absolute win-win deal for this goldmine of talent
Our latest work on transcription factors showing mechanistic insights into how they cooperate and its functional impact - great collaboration with Janosch Hennig's group at @embl who experimentally validated our predictions. Thanks Jussi Taipale for generating this great dataset!