Last 10 Commits for demotest2

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commit 06a68be1b597ec0a4b4192f438243be69196e800
Author: Breck Yunits <breck7@gmail.com> Date: Fri Sep 27 09:44:23 2024 -1000 diff --git a/index.scroll b/index.scroll index fb16bea..80fd38d 100644 --- a/index.scroll +++ b/index.scroll @@ -216,7 +216,7 @@ Thankfully, many people are experimenting with better ways for sharing science. https://research.arcadiascience.com/reimagining-scientific-publishing open notebooks on PubPeer -Scientific essays are intriguing because they are free to be everything papers are not: opinionated, informal, and dare I say, fun to read. Instead of every sentence being assembled by committee to avoid a reviewer’s wrath, essays offer an opportunity for unfettered scientific expression. We even already have a platform for distributing them: Twitter! Over the past few years, Twitter is where I’ve discovered my favorite scientific essays, some of which I’ll link here, here, and here. It doesn’t escape my attention that none of these were written by scientists in academia. While I’d love for this to change overnight, I realize that academics don’t have many tangible incentives to write. So for now, here’s my more concrete suggestion: PhD students should write part of their dissertation as a scientific essay. +Scientific essays are intriguing because they are free to be everything papers are not: opinionated, informal, and dare I say, fun to read. Instead of every sentence being assembled by committee to avoid a reviewer’s wrath, essays offer an opportunity for unfettered scientific expression. We even already have a platform for distributing them: Twitter! Over the past few years, Twitter is where I’ve discovered my favorite scientific essays, some of which I’ll link here, here, and here. It doesn’t escape my attention that none of these were written by scientists in academia. While I’d love for this to change overnight, I realize that academics don’t have many tangible incentives to write. So for now, here’s my more concrete suggestion: *PhD students should write part of their dissertation as a scientific essay*. http://jck.bio/learning-representations-of-life/ here match 0 https://ldeming.posthaven.com/sequencing-is-the-new-microscope here ------------------------------------------------------------
commit d96eaaf53d152e21c9f9b2f4129dc109dc0b9bcf
Author: root <root@hub.scroll.pub> Date: Fri Sep 27 19:43:01 2024 +0000 Updated header.scroll diff --git a/header.scroll b/header.scroll index 2cb9741..e199277 100644 --- a/header.scroll +++ b/header.scroll @@ -8,6 +8,6 @@ theme tufte homeButton viewSourceButton -container 800 +container 800px printTitle printDate ------------------------------------------------------------
commit 9b77f5ac69c0cbb9946631bf9a4a1c9376a2a3fb
Author: root <root@hub.scroll.pub> Date: Fri Sep 27 19:42:59 2024 +0000 Updated header.scroll diff --git a/header.scroll b/header.scroll index 46909c5..2cb9741 100644 --- a/header.scroll +++ b/header.scroll @@ -1,13 +1,13 @@ -importOnly -buildHtml -buildTxt - -metaTags -theme tufte - -homeButton -viewSourceButton - -container -printTitle -printDate +importOnly +buildHtml +buildTxt + +metaTags +theme tufte + +homeButton +viewSourceButton + +container 800 +printTitle +printDate ------------------------------------------------------------
commit 7ab17869f50f5b51a28fb947cfc875c79298cf9d
Author: root <root@hub.scroll.pub> Date: Fri Sep 27 19:42:31 2024 +0000 Updated index.scroll diff --git a/index.scroll b/index.scroll index 0c000f9..fb16bea 100644 --- a/index.scroll +++ b/index.scroll @@ -212,8 +212,17 @@ Here’s what I came up with: the ideal purpose of sharing science is to stimula Though Science Twitter is known for its disagreements, it’s safe to say we all agree on one thing: our current system for sharing science does not live up to our ideals. We could discuss the issues with scientific journals all day, but the problem with actual papers is they are both longer and emptier than we would like. Modern papers are filled with pages and pages of supplementary figures to appease cantankerous reviewers, while devoid of the thought-provoking speculations and musings once found in older literature. Most PhD dissertations, on the other hand, are little more than glorified lab notebooks, written more for obsessive completeness than for readability to fellow scientists. Thankfully, many people are experimenting with better ways for sharing science. Preprints let us share our work faster and theoretically open up peer review to the public, but are still largely beholden to the formatting and style whims of the traditional publishing system. Arcadia is piloting open notebooks on PubPeer, but for now, this is more at the institutional level rather than a choice an individual can make. Personally, I believe the long-term solution is not a single approach, but a buffet of options for every circumstance. Here, I’d like to advocate for a format that may appeal more to those in academia: the scientific essay. + https://www.arcadia.science/ Arcadia + https://research.arcadiascience.com/reimagining-scientific-publishing open notebooks on PubPeer + Scientific essays are intriguing because they are free to be everything papers are not: opinionated, informal, and dare I say, fun to read. Instead of every sentence being assembled by committee to avoid a reviewer’s wrath, essays offer an opportunity for unfettered scientific expression. We even already have a platform for distributing them: Twitter! Over the past few years, Twitter is where I’ve discovered my favorite scientific essays, some of which I’ll link here, here, and here. It doesn’t escape my attention that none of these were written by scientists in academia. While I’d love for this to change overnight, I realize that academics don’t have many tangible incentives to write. So for now, here’s my more concrete suggestion: PhD students should write part of their dissertation as a scientific essay. + http://jck.bio/learning-representations-of-life/ here + match 0 + https://ldeming.posthaven.com/sequencing-is-the-new-microscope here + match 1 + https://jsomers.net/i-should-have-loved-biology/ here + match 2 In the spirit of being the change I want to see, I have shared my own attempt here. It was certainly harder than I thought it would be! After years of writing papers, it was difficult to deprogram the jargon from my brain and write in a more accessible way. I also worry that people will think I’m boring or stupid or pretentious for believing my thoughts are worth sharing. But in the end, my goal was to write the essay I would’ve wanted to read as a 1st year grad student, and I feel I’ve put forth my best effort. ------------------------------------------------------------
commit 1cf1c1833cfb48d152a7e6a7218e4626858288af
Author: root <root@hub.scroll.pub> Date: Fri Sep 27 19:41:26 2024 +0000 Updated index.scroll diff --git a/index.scroll b/index.scroll index 0cd78bc..0c000f9 100644 --- a/index.scroll +++ b/index.scroll @@ -203,7 +203,8 @@ Happy exploring, ZC -Postscript: why write this? +# Postscript: why write this? + My original plan for my PhD dissertation was to staple all of my papers together. I know many people disagree with this practice, but this has always seemed patronizing to me. If I’ve published actual articles, why should I waste time re-writing them in a form nobody will read? Then some of my collaborators’ experiments failed, and during my newfound free time, I thought a lot about what it really means to share your science. Here’s what I came up with: the ideal purpose of sharing science is to stimulate discussion, inspire new ideas, and in the best cases, shift the collective consciousness. ------------------------------------------------------------
commit 547f6643deca60eeec7908b91d459d7d7c349f0a
Author: root <root@hub.scroll.pub> Date: Fri Sep 27 19:41:14 2024 +0000 Updated index.scroll diff --git a/index.scroll b/index.scroll index 27b6da8..0cd78bc 100644 --- a/index.scroll +++ b/index.scroll @@ -196,7 +196,7 @@ While live imaging followed by fixed in situ measurements might reveal how past By synthesizing the very best of microscopy and sequencing, the in situ technologies of the future will let us perceive biology at unprecedented resolution. And the new discoveries they enable will propel us to create even more advanced technologies that make the future a brighter place. -Why should we care about the future? I recently watched a video speculating on when the last human would live. The main premise was that if we manage to avoid cataclysmic events that wipe out all of humanity (a big if, but stay with me), humans will conservatively survive for at least a million years. And if we solve global warming and space travel and other future issues, we may survive many, many orders of magnitude beyond that. But given that we’ve existed for only 200 thousand years, it’s exceedingly likely we live right at the start of human history rather than towards the end. On the cosmic scale of human civilization, we are still discovering the foundational technologies. +Why should we care about the future? I recently watched a video speculating on when the last human would live. The main premise was that if we manage to avoid cataclysmic events that wipe out all of humanity (a big if, but stay with me), humans will conservatively survive for at least a million years. And if we solve global warming and space travel and other future issues, we may survive many, many orders of magnitude beyond that. But given that we’ve existed for only 200 thousand years, it’s exceedingly likely we live right at the start of human history rather than towards the end. *On the cosmic scale of human civilization, we are still discovering the foundational technologies*. https://youtu.be/LEENEFaVUzU when the last human would live Happy exploring, ------------------------------------------------------------
commit b1ed8aa04ec779079cda98df7ec01670a8969123
Author: root <root@hub.scroll.pub> Date: Fri Sep 27 19:41:06 2024 +0000 Updated index.scroll diff --git a/index.scroll b/index.scroll index 78d83f3..27b6da8 100644 --- a/index.scroll +++ b/index.scroll @@ -197,6 +197,7 @@ While live imaging followed by fixed in situ measurements might reveal how past By synthesizing the very best of microscopy and sequencing, the in situ technologies of the future will let us perceive biology at unprecedented resolution. And the new discoveries they enable will propel us to create even more advanced technologies that make the future a brighter place. Why should we care about the future? I recently watched a video speculating on when the last human would live. The main premise was that if we manage to avoid cataclysmic events that wipe out all of humanity (a big if, but stay with me), humans will conservatively survive for at least a million years. And if we solve global warming and space travel and other future issues, we may survive many, many orders of magnitude beyond that. But given that we’ve existed for only 200 thousand years, it’s exceedingly likely we live right at the start of human history rather than towards the end. On the cosmic scale of human civilization, we are still discovering the foundational technologies. + https://youtu.be/LEENEFaVUzU when the last human would live Happy exploring, ------------------------------------------------------------
commit 69a97d38a92ada6679670ab05a00d1142abd6028
Author: root <root@hub.scroll.pub> Date: Fri Sep 27 19:40:50 2024 +0000 Updated index.scroll diff --git a/index.scroll b/index.scroll index 65a20e6..78d83f3 100644 --- a/index.scroll +++ b/index.scroll @@ -192,7 +192,8 @@ multimodal.png While live imaging followed by fixed in situ measurements might reveal how past behavior affects cell state, we also want to learn how cell state predicts future behavior. Given that we can’t perform live imaging of a cell after fixed measurements, how can we accomplish this? One possibility is to train deep learning models that can foresee the future. Several years ago, Buggenthin and colleagues demonstrated that live imaging can be used to predict a stem cell’s lineage prior to the appearance of known molecular markers. In theory, you could train similar models for any cellular system with a heterogenous response, such as drug resistance or epigenetic reprogramming, and then perform in situ measurements at an early time point to identify which molecular states are most commonly associated with each predicted fate. https://www.nature.com/articles/nmeth.4182 Buggenthin and colleagues -Early days +# Early days + By synthesizing the very best of microscopy and sequencing, the in situ technologies of the future will let us perceive biology at unprecedented resolution. And the new discoveries they enable will propel us to create even more advanced technologies that make the future a brighter place. Why should we care about the future? I recently watched a video speculating on when the last human would live. The main premise was that if we manage to avoid cataclysmic events that wipe out all of humanity (a big if, but stay with me), humans will conservatively survive for at least a million years. And if we solve global warming and space travel and other future issues, we may survive many, many orders of magnitude beyond that. But given that we’ve existed for only 200 thousand years, it’s exceedingly likely we live right at the start of human history rather than towards the end. On the cosmic scale of human civilization, we are still discovering the foundational technologies. ------------------------------------------------------------
commit d09ed6fdfef3770ac120c70fa0b38d41e42a445d
Author: root <root@hub.scroll.pub> Date: Fri Sep 27 19:40:41 2024 +0000 Updated index.scroll diff --git a/index.scroll b/index.scroll index a864dff..65a20e6 100644 --- a/index.scroll +++ b/index.scroll @@ -192,4 +192,26 @@ multimodal.png While live imaging followed by fixed in situ measurements might reveal how past behavior affects cell state, we also want to learn how cell state predicts future behavior. Given that we can’t perform live imaging of a cell after fixed measurements, how can we accomplish this? One possibility is to train deep learning models that can foresee the future. Several years ago, Buggenthin and colleagues demonstrated that live imaging can be used to predict a stem cell’s lineage prior to the appearance of known molecular markers. In theory, you could train similar models for any cellular system with a heterogenous response, such as drug resistance or epigenetic reprogramming, and then perform in situ measurements at an early time point to identify which molecular states are most commonly associated with each predicted fate. https://www.nature.com/articles/nmeth.4182 Buggenthin and colleagues +Early days +By synthesizing the very best of microscopy and sequencing, the in situ technologies of the future will let us perceive biology at unprecedented resolution. And the new discoveries they enable will propel us to create even more advanced technologies that make the future a brighter place. + +Why should we care about the future? I recently watched a video speculating on when the last human would live. The main premise was that if we manage to avoid cataclysmic events that wipe out all of humanity (a big if, but stay with me), humans will conservatively survive for at least a million years. And if we solve global warming and space travel and other future issues, we may survive many, many orders of magnitude beyond that. But given that we’ve existed for only 200 thousand years, it’s exceedingly likely we live right at the start of human history rather than towards the end. On the cosmic scale of human civilization, we are still discovering the foundational technologies. + +Happy exploring, + +ZC + +Postscript: why write this? +My original plan for my PhD dissertation was to staple all of my papers together. I know many people disagree with this practice, but this has always seemed patronizing to me. If I’ve published actual articles, why should I waste time re-writing them in a form nobody will read? Then some of my collaborators’ experiments failed, and during my newfound free time, I thought a lot about what it really means to share your science. + +Here’s what I came up with: the ideal purpose of sharing science is to stimulate discussion, inspire new ideas, and in the best cases, shift the collective consciousness. + +Though Science Twitter is known for its disagreements, it’s safe to say we all agree on one thing: our current system for sharing science does not live up to our ideals. We could discuss the issues with scientific journals all day, but the problem with actual papers is they are both longer and emptier than we would like. Modern papers are filled with pages and pages of supplementary figures to appease cantankerous reviewers, while devoid of the thought-provoking speculations and musings once found in older literature. Most PhD dissertations, on the other hand, are little more than glorified lab notebooks, written more for obsessive completeness than for readability to fellow scientists. + +Thankfully, many people are experimenting with better ways for sharing science. Preprints let us share our work faster and theoretically open up peer review to the public, but are still largely beholden to the formatting and style whims of the traditional publishing system. Arcadia is piloting open notebooks on PubPeer, but for now, this is more at the institutional level rather than a choice an individual can make. Personally, I believe the long-term solution is not a single approach, but a buffet of options for every circumstance. Here, I’d like to advocate for a format that may appeal more to those in academia: the scientific essay. + +Scientific essays are intriguing because they are free to be everything papers are not: opinionated, informal, and dare I say, fun to read. Instead of every sentence being assembled by committee to avoid a reviewer’s wrath, essays offer an opportunity for unfettered scientific expression. We even already have a platform for distributing them: Twitter! Over the past few years, Twitter is where I’ve discovered my favorite scientific essays, some of which I’ll link here, here, and here. It doesn’t escape my attention that none of these were written by scientists in academia. While I’d love for this to change overnight, I realize that academics don’t have many tangible incentives to write. So for now, here’s my more concrete suggestion: PhD students should write part of their dissertation as a scientific essay. + +In the spirit of being the change I want to see, I have shared my own attempt here. It was certainly harder than I thought it would be! After years of writing papers, it was difficult to deprogram the jargon from my brain and write in a more accessible way. I also worry that people will think I’m boring or stupid or pretentious for believing my thoughts are worth sharing. But in the end, my goal was to write the essay I would’ve wanted to read as a 1st year grad student, and I feel I’ve put forth my best effort. + footer.scroll ------------------------------------------------------------
commit c6bfa5c5d6dc311e2ef606f9bd267750af88de35
Author: root <root@hub.scroll.pub> Date: Fri Sep 27 19:40:23 2024 +0000 Updated index.scroll diff --git a/index.scroll b/index.scroll index b6331f9..a864dff 100644 --- a/index.scroll +++ b/index.scroll @@ -184,5 +184,12 @@ Unfortunately for temporal measurements, one technology we won’t see any time https://www.science.org/doi/10.1126/science.abl5981 a paper combining calcium imaging to record electrical activity and RNA FISH to identify neuronal subtypes Since this approach to temporal measurements requires both live imaging and in situ technologies, we must also develop better methods for time-lapse imaging of multiple markers at once. One promising solution is a computational imputation technique known as label-free microscopy. To set up this technique, you first capture a basic imaging modality (e.g. brightfield, phase contrast) in parallel with immunostaining for cellular structures such as the nuclear lamina or mitochondria. Next, you train deep learning models to create mappings from the basic modality to each immunostain, and then lastly, perform continuous live imaging for the basic modality and apply your models to predict the immunostain at every time point. Though label-free microscopy is still at the proof-of-principle stage, it offers the promise of one day allowing you to predict the dynamics of any protein for “free” from basic live imaging data. + https://www.nature.com/articles/s41592-018-0111-2 label-free microscopy + +multimodal.png + caption Ounkomol et al. Nature Methods (2018) + +While live imaging followed by fixed in situ measurements might reveal how past behavior affects cell state, we also want to learn how cell state predicts future behavior. Given that we can’t perform live imaging of a cell after fixed measurements, how can we accomplish this? One possibility is to train deep learning models that can foresee the future. Several years ago, Buggenthin and colleagues demonstrated that live imaging can be used to predict a stem cell’s lineage prior to the appearance of known molecular markers. In theory, you could train similar models for any cellular system with a heterogenous response, such as drug resistance or epigenetic reprogramming, and then perform in situ measurements at an early time point to identify which molecular states are most commonly associated with each predicted fate. + https://www.nature.com/articles/nmeth.4182 Buggenthin and colleagues footer.scroll