Advantages of submitting first to the @biorxivpreprint : as an editor, I can share the entire paper with prospective reviewers to entice them to review it.
Let me tell you: this is a massive deal. Finding reviewers willing to commit to submit a review "soonish" (less than 2 months) is becoming tough.
I'm thinking about the FAIR (findable, accessible, interoperable, and reusable) principles of data. Much of our data is Western blots. Amongst colleagues, we were discussing how hard it would be to make it 'findable' which would require metadata schema, but I'm reconsidering it now.
I found a German paper from 2015 that has not really been cited and is more theory than practice. I wonder if anyone is actively working on this?
I'd be happy to participate.
'Correlation is not causation: this simple and uncontroversial statement has far-reaching implications. Defining and applying causality in biomedical research has posed significant challenges to the scientific community. In this perspective, we attempt to connect the partly disparate fields of systems biology, causal reasoning, and machine learning to inform future approaches in the field of systems biology and molecular medicine'
https://www.embopress.org/doi/full/10.1038/s44320-024-00041-w
Optimizing murine sample sizes for RNA-seq studies revealed from large-scale comparative analysis https://www.biorxiv.org/content/10.1101/2024.07.08.602525v1?med=mas
#statstab #132 P-Values are Random Variables
Thoughts: Ever-confusing, p-values are the bain of intro research method students. Maybe simulation is the key.
#stats #education #pvalues #NHST #simulation #edutstadon
#psychology #statistics
"Rodent chronic variable stress procedures: a disjunction between stress entity and impact on behaviour"
https://www.biorxiv.org/content/10.1101/2024.07.04.602063v1.full.pdf+html
We systematically investigated 350+ studies using chronic variable stress procedures in rodents and assessed the characteristics of the procedure (how many stressors they used, and how many different types, and for how long), then measured the reported effect size for those using behavioural tests as an outcome.
Some key disconcerting findings from our study
- the large majority of articles uses a unique protocol, and articles featuring the same protocol were from the same authors (aside from one case)
- 91% of articles don't provide any justification for their choice of procedure
This is scientifically and ethically troubling given CVS procedures deliberately impose suffering to animals.
- when looking at the outcome behavioural procedures measured in the studies (some of which impose further stress on the animals) we found very little correlation between effect size and the characteristics (eg length, strength) of the stress protocol. When there was a statistically significant effect, this was generally very small.
We conclude
"Most of the studies in our review sought evidence for interventions that would prevent or reverse the effects of chronic stress. But if we are to have any confidence that translational CVS studies provide a foundation for potential clinical interventions, we must take an evidence- and ethics-informed approach to their design."
#chronicVariableStress #stress #reproducibility #ethics #effectSize #translationalResearch #physiology
Sharing is caring!
#OpenScience practices (e.g. preprints) increase the impact of research articles as measured by citations. #preprint from Giovanni Colavizza and colleagues.
#preLight prepared by Priyanka Pant, Katarzyna Lepeta, Shalini Roy Choudhury & Reinier Prosee
#preLight 👉 https://prelights.biologists.com/highlights/an-analysis-of-the-effects-of-sharing-research-data-code-and-preprints-on-citations/
#sharing #preprints #code #data # collaboration #science #ResearchCulture
I cannot stress enough how good the Atkinson Hyperlegible font is: https://brailleinstitute.org/freefont
It's very pleasing on the eyes and it helps everyone understand and read your text, plus - it's completely free, even for commercial purposes!
What's not to love?
Reproducing bioimages and data analysis is a problem in the scientific world. No guidelines on how to do this, nor do journals have any recommendations for authors, until now! We have teamed up from around the world and developed a checklist to help make science reproducible👇
http://arxiv.org/abs/2302.07005
Reboosts appreciated
Just finished my first test using #shiny with #python!
I am thinking of creating a few of these for my image analysis course (because there is not enough stuff to do already 🤣)
Here it is
https://apps.nicolaromano.net/BitDepth/
And code here, feel free to modify/reuse at will!
https://github.com/nicolaromano/BIA4/tree/main/Apps/BitDepth
Do you use anything similar? Do you find it effective?
Basically I feel a little silly even posting this, because to me it's obvious. It's like there is a big red button that says "Fascism" and I'm like "do I really need to say that I think pushing that button is a terrible idea?"
But just in case? Under no circumstances should we push the big red button.
Elect Biden again and proceed to make him *miserable*
Better than being too miserable to get anything done.
#Introduction Hello. I'm a law prof, a philosopher, a progressive. I've deactivated #twitter and am searching for a new place to learn and to think out loud. #politics #law #democracy #elections #art #literature #history #science #books
#preprint alert 🚨
Can Large Language Models solve common #BioImageAnalysis coding tasks? And which #LLM performs best? 🙃🤓
Great collaboration with Christian Tischer, Jean-Karim Hériché and Nico Scherf
🔬🖥️🅰️ℹ️🤝🚀
https://www.biorxiv.org/content/10.1101/2024.04.19.590278v3
🌟 Exciting news! Just a week to go until #SciPy2024! 🎉 Stay tuned over the next few days as we reveal some of the amazing things our speakers will be presenting at the conference 👀
"But whilst it will have its benefits, the process of datafication also raises important methodological and ethical questions. Who has access to the data that is collected and why? How do the new data flows change everyday research practice? Are scientists being subjected to “dataveillance”, and if so, what does this mean for their privacy? To ensure that the scientific community embarks on a critically informed journey towards a datafied research ecosystem, these questions need to be addressed."
https://www.embopress.org/doi/full/10.1038/s44319-024-00153-2
“On AI and the commoditisation of design – Scott Riley”
https://www.scott.is/writing/about/ai-and-design
> That’s because I know the value good design can bring to a project, and it’s not the output. Design is about humans, about sense-making, systems thinking, and craft
« In this Comment, we emphasize the complexity of scientific software as a multifaceted socio-technical (and historically grown) system. We describe facets of software that we define as vantage points from which the different dimensions of software can be understood. The multifaceted nature of software implies that the work done by software has technical, legal, sociological and epistemic consequences. »
Senior lecturer at the Zhejiang-Edinburgh Joint Institute (ZJE) and Edinburgh University.
Undergraduate Programme Coordinator, Biomedical Informatics at ZJE.
I teach #imageanalysis & #dataanalysis with #RStats & #python. I study #heterogeneity in #pituitary (and other) cells.
I'm also very interested in #reproducibility and #openscience.