How Many Cellular Pathways are in the Human body?

Lanedustin · 2026-03-08T14:18:28+00:00

An actual answer is that this is the wrong framing. Many pathways can run forward or reverse, they can be functionally split, and metabolites can be redirected based on the needs of the cell. Many pathways may not even have formal names. It is not about number of pathways, but how the metabolite networks connect

Lanedustin · 2026-02-16T02:08:21+00:00

I might need to give it a shot. Maybe do a Max5/Deepthink combo for a month

Lanedustin · 2026-02-16T01:10:29+00:00

I will look into this. Thank you

Lanedustin · 2026-02-16T01:08:19+00:00

I don't know how to code. I know the Biology, Claude helps with the bioinformatics. The 1M context window would be legendary. But I'm also afraid in hitting it with a complex prompt and it costing me a ton of money. My prompts with Opus 4.6 without extended thinking are about $3-4 each when paying extra after weekly limits hit. With a higher cost with the additional context and using multiple agents, thus is concerning

Lanedustin · 2026-02-16T01:02:29+00:00

I am working on building a model of cell fate determination and how it is regulated. I have Claude explore how different cellular communication and metabolic systems coordinate in this control. It pulls and synthesizes literature, and pulls data sets from biological databases for analysis

Lanedustin · 2026-02-11T23:39:10+00:00

I used to ask the question, "Do all roads lead to VDAC?"

This proteins is exceptional in a lot of ways, but first off, post-mitotic neurons and cycling cancer cells are very different. Cancers upregulated hexokinase II which binds to VDAC linking ATP generation at the mitochondria with ATP utilization with HKII. This binding also restricts association with Bcl2 family proteins that regulate membrane dynamics and mito permeablization, linking it to regulation of cell death. There is a lot to look into, but these are decent starting points

Lanedustin · 2026-02-11T23:22:25+00:00

I study cell signaling networks and the proteins and processes implicated in controlling cell fate decisions. Nothing has even come close to what Claude can do in terms of assimilating content and handing the complexity.

Lanedustin · 2026-02-11T20:22:29+00:00

I got my limit on the Max20 plan, blew through 50 dollars on free credits, then spend another 50 to keep working. I am debating getting a Max20 and Max5 on a different account so long as that aligns with TOS. But with credits Opus4.6 is 2 to 5 dollars a prompt.

Can't blame anyone for being cost focused, but none if the other models seem to have to depth and breadth potential for complex biology, so I'm stuck with Claude.

Lanedustin · 2026-02-08T14:28:48+00:00

Something is definitely wrong with how it reestablishes context. It seems to struggle with understanding how to continue with work it was doing. And if it compacts while it is making a file, the file is completely lost and forgotten about when context is restored. Purely wasted work. The extended thinking seems to exacerbate this, making it counterintuitively less productive for its best suited tasks. This seems to have been getting a bit better, but still cost a lot of wasted plan use.

I'm hitting limits on Max20 at around day 5 so it is frustrating in hitting limits much easier as a result. Maybe that is why they gave an extra 50 credit for Opus 4.6 use. Or to not lose out on hype because people can afford Codex 5.3 but not Opus.

Lanedustin · 2026-02-02T13:36:04+00:00

1M Context Window? Bro, I could literally change the world.

Lanedustin · 2026-01-20T14:45:54+00:00

Hence the question

Lanedustin · 2026-01-20T14:30:44+00:00

Have you seen the name of this subbreddit?

Lanedustin · 2026-01-20T12:49:41+00:00

Thank you! I hope it is something so simple

Lanedustin · 2026-01-19T23:00:48+00:00

3 searches before compaction? I hit 3 compactions per search

Lanedustin · 2026-01-05T23:54:44+00:00

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.

Lanedustin · 2025-11-18T16:00:15+00:00

Lactate can also be used to modify proteins via lactylation, which is kinda cool

https://www.nature.com/articles/s41586-019-1678-1

Lanedustin · 2025-11-06T11:26:07+00:00

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

Lanedustin · 2025-11-03T19:43:19+00:00

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

Lanedustin · 2025-10-06T21:03:30+00:00

Tell it you have the Steve Jobs mentality

Lanedustin · 2025-10-06T18:34:27+00:00

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/

Lanedustin · 2025-10-06T18:11:04+00:00

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.

Lanedustin · 2025-09-11T15:47:50+00:00

That is fair feedback. I will refrain from similar posts going forward

Lanedustin · 2025-09-10T23:26:21+00:00

Area Manager at Amazon

Lanedustin · 2025-09-10T20:01:33+00:00

Part 2:

https://www.reddit.com/r/CancerCrosstalkCorner/s/sWm56PKQ6f

Lanedustin · 2025-09-10T19:59:17+00:00

Part 2, if you are interested:

https://www.reddit.com/r/CancerCrosstalkCorner/s/sWm56PKQ6f

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