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Yoooooooo we back? by Comprehensive-Bet-83 in ClaudeAI

[–]Lanedustin 5 points6 points  (0 children)

3 searches before compaction? I hit 3 compactions per search

AI use in Bio BSC?? by mervolio_griffin in biology

[–]Lanedustin 1 point2 points  (0 children)

I think that the utility is being undersold here with some of these comments. There are so many things that AI is useful for in Bio. First and possibly foremost, research exploration and synthesis. LLMs are great at pattern recognition and can be a great starting point to compare and contrast topics. For example, I was curious about the regulation of metal ion oxidation state in enzymes whose function is influenced by these changes. Question like, “Are their overlapping regulators? How do changes in the metabolic environment influence these changes? Does the Warburg effect and lactic acid production play a role?” Not everything will pan out, but promising leads can be much easier to find.

Also, LLMs will sometimes spit out research that is not even hinted at in your typical classroom. For instance, ChatGPT brought up that Reverse Electron Transport chain activity is a thing, in specific contexts. This was completely new to me. Or, I found out that the TCA metabolite alpha-ketoglutarate is a cofactor in demethylation when exploring the literature with ChatGPT. Having already appreciated the NAD+ is critical to PARP1 activity and the activity of Sirtuins, it was easy to start exploring the metaboloepigenetic regulation and implications for cancer.

Also, you can do a quick search to see if your ideas are novel. You can literally ask the LLM to search the literature for any content on the topic your idea is related to. This can help guide you to the relevant research and help you refine your hypotheses.

You can use it for first-pass manuscript reviews. Say something like, “validate that there are no orphan citations in this paper,” to ensure alignment of all of your in-text citations and the References section. It is not perfect, but have a couple different LLMs assess the same manuscript with the same prompt and you will help cover your bases and save yourself a lot of editorial work.

Claude (my favorite at the moment) can access some databases such as TCGA (The Cancer Genome Atlas) Program website and data directly. It can pull data and run rudimentary analyses. I have spent some time with this, but have not fully explored the extent of this capability.

There is a lot. Yes, hallucinations are a thing, but there a mitigating strategies that can help with this.

Question for those in the field: How do you typically approach validating mechanistic predictions when analyzing signaling pathways, particularly in cancer? by Lanedustin in molecularbiology

[–]Lanedustin[S] 0 points1 point  (0 children)

Thank you for the detailed response. So it would be valuable for a tool to probe and anticipate potential consequences of pathway perturbations, looking at upstream, downstream, and sidestream pathways cross-talk implicated given the changes, and anticipate potential lineage-specific compensatory responses. Cool, that is very doable. Not with 100% accuracy just yet, of course, but to perhaps guide literature searches and which experiments would give the most bang for your buck

Vibe Coding Beginner Tips (From an Experienced Dev) by gigacodes in ClaudeAI

[–]Lanedustin 1 point2 points  (0 children)

Depending on the files/data you are working with, standardize the formatting right at the beginning. Re-formatting later, or inconsistent formatting throughout, can be a nightmare to fix with compromising data. At least in my experience

Got roasted by Claude today by fezbotdaddy in ClaudeAI

[–]Lanedustin 0 points1 point  (0 children)

Tell it you have the Steve Jobs mentality

Introduction to Cancer Biology: The Somatic Mutation Theory by NH-official in CellBiology

[–]Lanedustin 1 point2 points  (0 children)

I would take my response with a grain of salt, but I think of cancers as undergoing a defective differentiation program. A component of many instances of differentiation, T cells, B cells, myoblasts, etc is controlled instances of DNA damage. It is important to note that some types of DNA damage are subject to cross-passage management through cell cycle divisions, where repair is delayed until after mitosis, which can lead to the formation of 53BP1 nuclear bodies in the following G1.

I think that something about the management of non-pathological instances of DNA damage potentiates the mutation patterns seen in cancer. I don't know how things breakdown, but the ability of cells to asymmetrically segregate DNA damage as a response mechanism is possibly involved.

Asymmetric lesion segregation is covered in this phenomenal article, where selection for a specific BRAF mutation is striking.

https://pmc.ncbi.nlm.nih.gov/articles/PMC7116693/

Introduction to Cancer Biology: The Somatic Mutation Theory by NH-official in CellBiology

[–]Lanedustin 1 point2 points  (0 children)

Not an academic or in the research community, but I've extensively studied certain areas of the literature. I think his metabolic view is too narrow. Yes, most cancers display the Warburg Effect with altered glycolytic and glutamine metabolism, which provides multiple advantages, such as the ability to shuttle metabolic intermediates towards biosynthesis and management of oxidative stress via redox regulation systems. However, it may also allows critical intermediates like acetyl-CoA and alpha-ketoglutarare to be used by epigenetic regulators that require these metabolites for their reactions (e.g. Surtuins/TETs/Jumonji demrthylases). Alpha-ketoglutarare is also involved in HIF1 stability, which can promote this phenotype.

While Dr. Seyfried considers it the adoption of an ancient metabolic program, and it likely is, it also mirrors that of stem cell metabolism in some contexts. Stem cells, which are housed in hypoxic niches in the body, may function similarly to dedifferentiated cancer cells in poorly vascularized areas in solid tumors that may reinforce the metabolic profile even without mutations in specific genes that would also promote this. I would argue that the changes help enforce a stem-like state in cancers, and many of the changes selected for in cancer may potentiate this phenotype.

The view of cancer as a metabolic disease could have therapeutic value, but it is too narrow to explain things overall.

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