A friend of mine is getting ready to do some experiments involving purified human proteins expressed in E. coli, and she asked me if I knew anything about protein misfolding - apparently, proteins sometimes misfold when expressed in foreign vectors such as E. coli. Unfortunately, I didn't, but a Google search hit brought up an explanation that's really not that surprising when you think about it, and has to do with the fact that many proteins fold correctly only with the help of chaperone proteins or cofactors. Obviously, this can be a big problem for an experimentalist who wants to get usable amounts of a specific, correctly folded protein.
Does anyone know where to find good information about this problem or have suggestions for how to get around it (with or without changing vectors - I'm not sure if E.coli is a crucial part of the study or not)? The document I linked has some solutions but I'm wondering if there are any resources or "easy" tips out there I can forward along.
Showing posts with label questions. Show all posts
Showing posts with label questions. Show all posts
Thursday, March 13, 2008
Tuesday, February 26, 2008
Tools for analyzing "lists" in biology
My latest research is focused on cluster/list annotation in biology. Given a cluster or list of genes or proteins that were grouped together using some metric (expression profile, sequence or structure similarity, interactions, etc), how can you discover descriptive terms or labels for that cluster? This seems to be a common question, and yet I've had trouble finding tools that help you do what I am specifically trying to do (investigation of a list of biological entities). I've found many that can give you tons of information for single genes or proteins, which I don't consider that helpful, and a few that can give you information for a group, but these are either organism specific or limited to one or two types of data (e.g. GO terms).
Since I am developing a method to do this based on text, I'd like to be able to compare my method to existing ones that solve the same problem. What I am looking for is two or three available methods that give you information relevant to a list of biological entities from multiple species, at least one of which uses literature or text-mining. Does anyone know of such methods, or have ideas of where to look? Various PubMed and Google searches have failed me!
Unrelated, but also done today: Submitted the PSB proposal to Nature Precedings as per several of your requests. Will update once word is back from their review process.
Since I am developing a method to do this based on text, I'd like to be able to compare my method to existing ones that solve the same problem. What I am looking for is two or three available methods that give you information relevant to a list of biological entities from multiple species, at least one of which uses literature or text-mining. Does anyone know of such methods, or have ideas of where to look? Various PubMed and Google searches have failed me!
Unrelated, but also done today: Submitted the PSB proposal to Nature Precedings as per several of your requests. Will update once word is back from their review process.
Friday, February 22, 2008
Science journal feedmixes
The topic of literature review came up at a recent group meeting. Our advisor receives a number of print subscriptions to journals, but these often languish in some forgotten corner. Even when they are brought out of the depths, it seems a daunting task to leaf through them to find articles of interest to each student. Since everyone is on the interwebs, it is much easier (and complete) to get updates on relevant articles through a website or email, peruse the titles and blurbs online, and then decide what to actually sit down and read. There are a few problems with this, however.
I've set up a feedmixer for science journals and related information using Feed Digest. It's little more than an aggregator right now so it doesn't really address those problems. If anyone knows of any cool tricks to help sift through the ridiculous amounts of information we're supposed to keep up with, without losing the unexpected gems, I'd love to hear it!
Update: A new tool called Persai claims to learn your preferences through what you accept and what you reject (review on Slate), and filters your feeds accordingly. I'm not sure it will help with issue #2, but it's probably just an irreconciliable trade-off between #1 and #2. Perhaps the solution is to have a couple different pages set up with Persai - narrow ones for specific fields or interests, and broader ones for the science "pleasure reading"!
- Getting alerts from journals, search engines, or aggregators like Faculty of 1000 still usually produces too many articles to sift through.
- To limit the amount of junk you get, you provide keywords - but, if you're like me, you will browse through unlikely articles in Science or Nature or PLoS ONE on a regular basis because they look interesting, so keywords will filter these out.
I've set up a feedmixer for science journals and related information using Feed Digest. It's little more than an aggregator right now so it doesn't really address those problems. If anyone knows of any cool tricks to help sift through the ridiculous amounts of information we're supposed to keep up with, without losing the unexpected gems, I'd love to hear it!
Update: A new tool called Persai claims to learn your preferences through what you accept and what you reject (review on Slate), and filters your feeds accordingly. I'm not sure it will help with issue #2, but it's probably just an irreconciliable trade-off between #1 and #2. Perhaps the solution is to have a couple different pages set up with Persai - narrow ones for specific fields or interests, and broader ones for the science "pleasure reading"!
Friday, February 1, 2008
Ignorance of the masses - should we worry?
This is the second somewhat negative post I've written on Open Science. You might say I've moved from the Honeymoon phase to the phase where all you can do is judge and criticize and focus on the bad. Let's hope I move on to the mature, balanced, productive phase soon! In any case, I still highly support the concept of Open Science and want to see it grow, but right now I am using this blog to explore both sides.
There are many issues and questions surrounding Open Science which I have been slowly familiarizing myself with over the last few weeks. Some things, like intellectual property rights, privacy, and scooping, are obvious and comprise the bulk of the debate. I started thinking about a different issue related to Open Science recently, mostly inspired by the escalating battle between evolution and Creationism/ID and the comments of former presidential hopeful Mike Huckabee. The following may be more politically charged than appropriate for a blog like this, so consider yourself warned.
It boils down to this: the public is essentially ignorant. What I mean is that most people know a lot about very few topics, and very little about everything else. Most of what they learn about everything else comes from the media. I won't even go into the problems with our education system or the fact that most Americans have a very strange idea of what science is. The problem is that it doesn't take much for a study to be misinterpreted, or science to be misrepresented. Mainstream media will go for the most sensational spin. Think about all those "health" and "wellness" magazines that immediately latch on to and exaggerate the latest studies on coffee, supplements, and compounds in food, regardless of where they were published.
If Open Science is fully realized, bleeding edge scientific research will be at everyone's fingertips. Preliminary results, perhaps before appropriate controls are performed, will be available to people who don't have the training (or desire) to distinguish between rigorously obtained findings and works in progress. Prior to this, the only science accessible to the world outside went through the filter of a peer-review journal (and presumably is already summarized and interpreted in the way that best describes all the data and findings in the entire study). Without a filter, is there more risk for misinterpretation and misrepresentation by those outside the scientific sphere? If so, what precautions can we take to mitigate it?
There are many issues and questions surrounding Open Science which I have been slowly familiarizing myself with over the last few weeks. Some things, like intellectual property rights, privacy, and scooping, are obvious and comprise the bulk of the debate. I started thinking about a different issue related to Open Science recently, mostly inspired by the escalating battle between evolution and Creationism/ID and the comments of former presidential hopeful Mike Huckabee. The following may be more politically charged than appropriate for a blog like this, so consider yourself warned.
It boils down to this: the public is essentially ignorant. What I mean is that most people know a lot about very few topics, and very little about everything else. Most of what they learn about everything else comes from the media. I won't even go into the problems with our education system or the fact that most Americans have a very strange idea of what science is. The problem is that it doesn't take much for a study to be misinterpreted, or science to be misrepresented. Mainstream media will go for the most sensational spin. Think about all those "health" and "wellness" magazines that immediately latch on to and exaggerate the latest studies on coffee, supplements, and compounds in food, regardless of where they were published.
If Open Science is fully realized, bleeding edge scientific research will be at everyone's fingertips. Preliminary results, perhaps before appropriate controls are performed, will be available to people who don't have the training (or desire) to distinguish between rigorously obtained findings and works in progress. Prior to this, the only science accessible to the world outside went through the filter of a peer-review journal (and presumably is already summarized and interpreted in the way that best describes all the data and findings in the entire study). Without a filter, is there more risk for misinterpretation and misrepresentation by those outside the scientific sphere? If so, what precautions can we take to mitigate it?
Friday, January 25, 2008
Is the danger of being scooped field-dependent?
The students in my program get together once in a while for what we call "Researchome", also known fondly as "dinner-ome", originally conceived as a casual forum in which students could present their research or other topics of interest to other students, while getting dinner for free. But without someone to present, there is no justification to have Researchome, so rather than deprive a dozen grad students of free food, I threw together a quick presentation of Open Science and my proposal for PSB for our Researchome last night.
Biomedical informatics students are a smart bunch, so there was some great discussion. Naturally, the concern over getting scooped came up, and while I was quick to pooh-pooh it as a naive/narcissistic fear, the others were fairly adamant that it was a valid concern. Several gave personal anecdotes. And the picture that started to emerge was one where the danger of being scooped was highly dependent on the field you were in - theoretical vs. applied, basic vs. translational, science vs. medicine, all of which may put different emphasis on the idea vs. the implementation.
According to one of the students at the Researchome, in theoretical disciplines such as math or physics, credit is given as soon as an idea is recorded. But in fields like cell biology, just having the idea for an experiment or a hypothesis is not enough; instead, you must conduct the experiment and demonstrate successful results through a peer-reviewed publication before credit is given. Because of this, people in these fields are more reluctant to be open about their research before it has been published, and getting scooped can have real consequences for someone's career and funding. In my limited explorations of the world wide open science web, it seems as if a significant portion of those participating are chemists. Is getting scooped less of a concern in chemistry than it is in, say, molecular biology, and, if so, why? If there is a discrepancy between fields in the danger of being scooped, how should this be addressed as the open science community moves forward? Is it possible to change the standards by which success and intellectual credit are determined?
Aside from this interesting issue, some valid points were brought up concerning the proposal for an open science session at PSB. One is that the audience at PSB is by and large composed of scientists who don't generate their own data, but use the data generated by others. A lot of high-throughput, -omics, and bioinformatics-minded people. Therefore, open data and open source will probably be of greater interest to them than the more overarching idea of open notebook science. Focusing on standards, exchange formats, and tools and methodologies for conducting open science may be a good approach.
The other consensus that the students came to was that open science is so broad and important a topic that it should be featured as a session at a much larger conference, such as ISMB or AMIA. Many were bemused as to why I chose what is arguably a niche conference as a venue for open science. My rationale at this point is that it is the soonest we could possibly organize a meeting on open science jointly with an established conference, and I think the audience is relevant enough for it to be productive. Being smaller, it may also be a good stepping stone towards a bigger meeting, and I wouldn't be surprised if some efforts began for that before PSB 2009 comes around.
Many thanks to the students who attended the Researchome for their feedback. I'll be working on a draft of the proposal over the next couple days.
Biomedical informatics students are a smart bunch, so there was some great discussion. Naturally, the concern over getting scooped came up, and while I was quick to pooh-pooh it as a naive/narcissistic fear, the others were fairly adamant that it was a valid concern. Several gave personal anecdotes. And the picture that started to emerge was one where the danger of being scooped was highly dependent on the field you were in - theoretical vs. applied, basic vs. translational, science vs. medicine, all of which may put different emphasis on the idea vs. the implementation.
According to one of the students at the Researchome, in theoretical disciplines such as math or physics, credit is given as soon as an idea is recorded. But in fields like cell biology, just having the idea for an experiment or a hypothesis is not enough; instead, you must conduct the experiment and demonstrate successful results through a peer-reviewed publication before credit is given. Because of this, people in these fields are more reluctant to be open about their research before it has been published, and getting scooped can have real consequences for someone's career and funding. In my limited explorations of the world wide open science web, it seems as if a significant portion of those participating are chemists. Is getting scooped less of a concern in chemistry than it is in, say, molecular biology, and, if so, why? If there is a discrepancy between fields in the danger of being scooped, how should this be addressed as the open science community moves forward? Is it possible to change the standards by which success and intellectual credit are determined?
Aside from this interesting issue, some valid points were brought up concerning the proposal for an open science session at PSB. One is that the audience at PSB is by and large composed of scientists who don't generate their own data, but use the data generated by others. A lot of high-throughput, -omics, and bioinformatics-minded people. Therefore, open data and open source will probably be of greater interest to them than the more overarching idea of open notebook science. Focusing on standards, exchange formats, and tools and methodologies for conducting open science may be a good approach.
The other consensus that the students came to was that open science is so broad and important a topic that it should be featured as a session at a much larger conference, such as ISMB or AMIA. Many were bemused as to why I chose what is arguably a niche conference as a venue for open science. My rationale at this point is that it is the soonest we could possibly organize a meeting on open science jointly with an established conference, and I think the audience is relevant enough for it to be productive. Being smaller, it may also be a good stepping stone towards a bigger meeting, and I wouldn't be surprised if some efforts began for that before PSB 2009 comes around.
Many thanks to the students who attended the Researchome for their feedback. I'll be working on a draft of the proposal over the next couple days.
Wednesday, January 16, 2008
Open Science at PSB 2009?
I attended a seminar today where we came up with a list of ideas for sessions for the 2009 meeting of the Pacific Symposium on Biocomputing (PSB). This group of people organized a session at PSB 2008 called "Multi-scale modeling", so many of the ideas were related to computational modeling. But since I am interested in Open Science, I asked whether there would be interest in having an Open Science session at PSB.
PSB is a pretty prestigious conference that prides itself on covering only the "hot topics" in biology and biocomputing. Combine that with their locale (Hawaii), and you can imagine it is fairly difficult to get accepted. But even though a session on Open Science would differ from their traditional sessions (less primary research papers, more tutorials / descriptions of experiences / discussion), I think it would be great to talk about Open Science there, since A) PSB is prestigious, B) attendees are probably pretty forward-thinking, C) by Jan 2009, we will be ready to have some really productive discussion, and D) did I mention Hawaii?
The deadline for submitting a session proposal is Feb 8th, which is in only a couple weeks. If there is support for this, I will try to carry it through. Here is the call for papers, which includes guidelines for what makes a good session, and responsibilities of a session chair. I'm not sure that I would be the best choice for a session chair since I have not participated in an open science endeavors yet and the session chair is required to give a 1 hr tutorial on the session topic, so if anyone is interested in being the session chair, please let me know! Ideas for what kind of papers could be solicited would also be appreciated.
PSB is a pretty prestigious conference that prides itself on covering only the "hot topics" in biology and biocomputing. Combine that with their locale (Hawaii), and you can imagine it is fairly difficult to get accepted. But even though a session on Open Science would differ from their traditional sessions (less primary research papers, more tutorials / descriptions of experiences / discussion), I think it would be great to talk about Open Science there, since A) PSB is prestigious, B) attendees are probably pretty forward-thinking, C) by Jan 2009, we will be ready to have some really productive discussion, and D) did I mention Hawaii?
The deadline for submitting a session proposal is Feb 8th, which is in only a couple weeks. If there is support for this, I will try to carry it through. Here is the call for papers, which includes guidelines for what makes a good session, and responsibilities of a session chair. I'm not sure that I would be the best choice for a session chair since I have not participated in an open science endeavors yet and the session chair is required to give a 1 hr tutorial on the session topic, so if anyone is interested in being the session chair, please let me know! Ideas for what kind of papers could be solicited would also be appreciated.
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