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Mathematical statistics

Created page Mathematical statistics.

The main purpose right now is to provide a link to the statistical computing software "R". I would like to provide enough information on Azimuth for any math professor or PhD to refresh essential knowledge about statistics, find useful software and relevant datasets and eventually do some toy analysis on her own. Like, e.g., a statistical analysis of temperature measurements. Maybe I'm overly naive, but I would like to enrich the "global warming is obviously a reality" vs. "global warming is obviously a hoax" discussion with some statements along the line "here are some data sets, here are some simple statistical analysis tools, that's what they say". At least some people with an engineering/scientific background should be able to, and interested in, taking a look for themselves. If it's easy enough to find the necessary background material. Amen.

Comments

  • 1.

    I don't want to stop you doing anything, this is just my personal perspective:

    This is probably something Nathan Urban can comment on more knowledgeably, but my limited understanding is that some of the nastiest, and most controversial, statistics comes in things like correcting classes of data (eg, "correcting" temperature readings from ocean buoys that were calibrated years ago in a way that's different to other sensors), extrapolating from incredibly lmited geographical data historically and even deciding which data to throw out because it's too unreliable. Combine that with the fact that a lot of the effects so far are small enough that the statistical signal is going to be on the edge of significance...

    Certainly, I made a pre-emptive decision years ago never to do any climate stats myself (unless I get a job doing it full time) because I don't think I'll be able to sink enough time into it to figure out these things and if which ones are valid.

    Comment Source:I don't want to stop you doing anything, this is just my personal perspective: This is probably something Nathan Urban can comment on more knowledgeably, but my limited understanding is that some of the nastiest, and most controversial, statistics comes in things like correcting classes of data (eg, "correcting" temperature readings from ocean buoys that were calibrated years ago in a way that's different to other sensors), extrapolating from incredibly lmited geographical data historically and even deciding which data to throw out because it's too unreliable. Combine that with the fact that a lot of the effects _so far_ are small enough that the statistical signal is going to be on the edge of significance... Certainly, I made a pre-emptive decision years ago never to do any climate stats myself (unless I get a job doing it full time) because I don't think I'll be able to sink enough time into it to figure out these things and if which ones are valid.
  • 2.

    ...some of the nastiest, and most controversial, statistics comes in things like correcting classes of data...

    Yes, that's a problem. But there are also discussions about the statistical analysis and interpretation of the data (and not only by our friend LM), and just as a true applied mathematician would I chose to attack the problem that I could help to solve eventually, and not the hardest one :-)

    Comment Source:<blockquote> <p> ...some of the nastiest, and most controversial, statistics comes in things like correcting classes of data... </p> </blockquote> Yes, that's a problem. But there are also discussions about the statistical analysis and interpretation of the data (and not only by our friend LM), and just as a true applied mathematician would I chose to attack the problem that I could help to solve eventually, and not the hardest one :-)
  • 3.

    Tim wrote:

    I would like to provide enough information on Azimuth for any math professor or PhD to refresh essential knowledge about statistics, find useful software and relevant datasets and eventually do some toy analysis on her own.

    Even better, if you explain things well enough that a smart student can understand you, we may lure some smart students into the subject of climate change. Doing a "toy analysis" on ones own can be a first step towards taking more courses and moving towards a career in this subject. I'm a firm believer in getting people interested in things while they're still students, before they're locked into a career path.

    Comment Source:Tim wrote: >I would like to provide enough information on Azimuth for any math professor or PhD to refresh essential knowledge about statistics, find useful software and relevant datasets and eventually do some toy analysis on her own. Even better, if you explain things well enough that a smart student can understand you, we may lure some smart students into the subject of climate change. Doing a "toy analysis" on ones own can be a first step towards taking more courses and moving towards a career in this subject. I'm a firm believer in getting people interested in things while they're still students, before they're locked into a career path.
  • 4.
    edited November 2010

    Sure, I'll try, of course. Why did I write professors instead of students? Thinking of myself, for the first couple of years I concentrated on getting all the credits I needed to move on as fast as I could. Then, I concentrated on job opportunities (roughly 1.5 years before I got my Diplom), both in academia and outside. I chose the subject of my Diplom to include numerical and statistical analysis because that is applied and includes working with computer code - that was during the dot-com-bubble. So, frankly, choosing a subject and specializing in it because it seemed to be interesting enough was, at most, secondary. That's the reason why I did not specialize in AQFT, for example :-)

    So, I did expect that it would be much easier for someone with tenure to try something new, with unclear prospects which career impacts that may have. And since I assume of course that everyone is like me, I'd say that to get students interested you should somehow explain how a carreer in the subject would look like :-)

    E.g., which academic institutions would hire an "environmental mathematician"? (We know one already, of course, from Nathan Urban).

    Comment Source:Sure, I'll try, of course. Why did I write professors instead of students? Thinking of myself, for the first couple of years I concentrated on getting all the credits I needed to move on as fast as I could. Then, I concentrated on job opportunities (roughly 1.5 years before I got my Diplom), both in academia and outside. I chose the subject of my Diplom to include numerical and statistical analysis because that is applied and includes working with computer code - that was during the dot-com-bubble. So, frankly, choosing a subject and specializing in it because it seemed to be interesting enough was, at most, secondary. That's the reason why I did not specialize in AQFT, for example :-) So, I did expect that it would be much easier for someone with tenure to try something new, with unclear prospects which career impacts that may have. And since I assume of course that everyone is like me, I'd say that to get <i>students</i> interested you should somehow explain how a carreer in the subject would look like :-) E.g., which academic institutions would hire an "environmental mathematician"? (We know one already, of course, from Nathan Urban).
  • 5.

    While I do climate statistics, it's mostly parameter estimation (i.e., Bayesian regression with a climate model as the regression function). I'm not as expert on the gory details that go into synthesizing major data products like the surface or ocean temperature records. There are amateurs who look at that sort of thing, but it's a very major undertaking.

    For an interested amateur to get their feet wet with climate statistics, I'd start out by analyzing the features existing data products without getting too far into how those data products were created. This could be trend analysis (regression), looking at correlations between different data sets (or different parts of the same data set), principal component analysis of climate patterns, etc.

    Unfortunately I can't recommend too many climate statistics blogs, because they're rare, and tend to degenerate into partisanship like most climate blogs do, or else, shall we say, "potentially revolutionary contributions to climate science". One possibility is Climate Charts and Graphs. If one does want to get into the surface temperature data sets, there is a SkepticalScience page with links to various efforts. There is also ClearClimateCode and Wood for Trees. A professional effort is Surface Temperatures (and blog), but there's not much content yet.

    I don't know who would hire an "environmental mathematician". A math department, I suppose. I think I had an easier time getting hired to do climate science because I have a physics Ph.D., not a math Ph.D. But my old postdoctoral advisor, Klaus Keller, did hire a math Ph.D. for a postdoc before I was hired. (His thesis was in applied mathematics, on numerical fluid dynamics applied to environmental problems.) Klaus is open to hiring non-climate scientists with strong quantitative backgrounds, because his group does work that is non-traditional for climate science (statistical data-model comparisons and economic analyses aren't too common), and for that one might actually prefer a "generic problem solver". But I want to emphasize that is a rare example. Most geoscience jobs are realistically open only to trained geoscientists.

    There are applied math programs who hire people to do geophysical mathematics, such as the Courant Institute. That's mostly fluid flow, dynamical systems theory, etc. One could also find success with a numerical analysis background. But it's harder to break in for people with a different mathematical background. One option could be to poke around the participant affiliations of workshops (such as this one or this one) to see if you can find mathematicians or theoretical physicists, who employs them, and what their training is in.

    Frankly, if a student wants to pursue an environmental science career, I wouldn't recommend that they be supervised by an advisor who isn't a scientist, unless they really care more about the math than the application. (At least at the Ph.D. level. A math undergrad could more easily jump into science for grad school.) As soon as you get into applied field, employers want to see a student who has "street cred" as a geoscientist, or at least a physical scientist. It is possible for a math Ph.D. to jump into the field, but I wouldn't guarantee it, unless their thesis is co-supervised by a card-carrying scientist, or they otherwise closely collaborate with one to publish papers. If they're happy being in a math department writing grant proposals in mathematics, that's another matter, but I'd imagine their thesis work would have to shine on its mathematical merits more than its scientific relevance.

    "Toy analyses" are good for undergrad senior theses, though ... but I would still run the projects past a professional scientist.

    Comment Source:While I do climate statistics, it's mostly parameter estimation (i.e., Bayesian regression with a climate model as the regression function). I'm not as expert on the gory details that go into synthesizing major data products like the surface or ocean temperature records. There are amateurs who look at that sort of thing, but it's a very major undertaking. For an interested amateur to get their feet wet with climate statistics, I'd start out by analyzing the features existing data products without getting too far into how those data products were created. This could be trend analysis (regression), looking at correlations between different data sets (or different parts of the same data set), principal component analysis of climate patterns, etc. Unfortunately I can't recommend too many climate statistics blogs, because they're rare, and tend to degenerate into partisanship like most climate blogs do, or else, shall we say, "potentially revolutionary contributions to climate science". One possibility is [Climate Charts and Graphs](http://chartsgraphs.wordpress.com/). If one does want to get into the surface temperature data sets, there is a [SkepticalScience page](http://www.skepticalscience.com/print.php?n=287) with links to various efforts. There is also [ClearClimateCode](http://clearclimatecode.org/) and [Wood for Trees](http://www.woodfortrees.org/). A professional effort is [Surface Temperatures](http://www.surfacetemperatures.org/) (and [blog](http://surfacetemperatures.blogspot.com/)), but there's not much content yet. I don't know who would hire an "environmental mathematician". A math department, I suppose. I think I had an easier time getting hired to do climate science because I have a physics Ph.D., not a math Ph.D. But my old postdoctoral advisor, Klaus Keller, did hire a math Ph.D. for a postdoc before I was hired. (His thesis was in applied mathematics, on numerical fluid dynamics applied to environmental problems.) Klaus is open to hiring non-climate scientists with strong quantitative backgrounds, because his group does work that is non-traditional for climate science (statistical data-model comparisons and economic analyses aren't too common), and for that one might actually prefer a "generic problem solver". But I want to emphasize that is a rare example. Most geoscience jobs are realistically open only to trained geoscientists. There are applied math programs who hire people to do geophysical mathematics, such as the Courant Institute. That's mostly fluid flow, dynamical systems theory, etc. One could also find success with a numerical analysis background. But it's harder to break in for people with a different mathematical background. One option could be to poke around the participant affiliations of workshops (such as [this one](http://www.ipam.ucla.edu/programs/cl2010/) or [this one](http://www.newton.ac.uk/programmes/CLP/ws.html)) to see if you can find mathematicians or theoretical physicists, who employs them, and what their training is in. Frankly, if a student wants to pursue an environmental science career, I wouldn't recommend that they be supervised by an advisor who isn't a scientist, unless they really care more about the math than the application. (At least at the Ph.D. level. A math undergrad could more easily jump into science for grad school.) As soon as you get into applied field, employers want to see a student who has "street cred" as a geoscientist, or at least a physical scientist. It is possible for a math Ph.D. to jump into the field, but I wouldn't guarantee it, unless their thesis is co-supervised by a card-carrying scientist, or they otherwise closely collaborate with one to publish papers. If they're happy being in a math department writing grant proposals in mathematics, that's another matter, but I'd imagine their thesis work would have to shine on its mathematical merits more than its scientific relevance. "Toy analyses" are good for undergrad senior theses, though ... but I would still run the projects past a professional scientist.
  • 6.

    Thanks! That's a lot of information...

    I'd start out by analyzing the features (of) existing data products without getting too far into how those data products were created.

    Good point, I like to program and figure out if I can do it myself, so it's not just a means to an end to me - if one is interested in the analysis of the data without being bothered by implementation details, I'd say that learning how to use a software like R is the best way to start.

    "Toy analyses" are good for undergrad senior theses, though ... but I would still run the projects past a professional scientist.

    I would never recommend to anyone to play around all by herself, without the help, guidance or cooperation of an expert, especially if all this is about the first stepping stone of a career in academia. I consider these toy experiments as a way to learn some background knowledge in order to be able to talk to and understand the experts: Maybe, with much luck and effort, someone like John could, sometime in the future, point his students to some pages on Azimuth as a preparation for a collaborative work with an expert in geoscience.

    Comment Source:Thanks! That's a lot of information... <blockquote> <p> I'd start out by analyzing the features (of) existing data products without getting too far into how those data products were created. </p> </blockquote> Good point, I like to program and figure out if I can do it myself, so it's not just a means to an end to me - if one is interested in the analysis of the data without being bothered by implementation details, I'd say that learning how to use a software like R is the best way to start. <blockquote> <p> "Toy analyses" are good for undergrad senior theses, though ... but I would still run the projects past a professional scientist. </p> </blockquote> I would never recommend to anyone to play around all by herself, without the help, guidance or cooperation of an expert, especially if all this is about the first stepping stone of a career in academia. I consider these toy experiments as a way to learn some background knowledge in order <b>to be able to talk to and understand the experts</b>: Maybe, with much luck and effort, someone like John could, sometime in the future, point his students to some pages on Azimuth as a preparation for a collaborative work with an expert in geoscience.
  • 7.

    Is the "Mathematical Statistics" page an appropriate place to put references to books on applied statistics?

    Comment Source:Is the "Mathematical Statistics" page an appropriate place to put references to books on applied statistics?
  • 8.
    edited November 2010

    Nathan wrote:

    Is the "Mathematical Statistics" page an appropriate place to put references to books on applied statistics?

    Sure, that'd be great!

    Thanks for the information on the — possibly not yet existent? — job opportunities for "environmental mathematicians". I will have to be a bit careful accepting new grad students when I return to Riverside 2 years from now: I don't want to take idealistic students and give them an education with no job prospects. But on the other hand, I'm just barely starting to figure out what I want to do, so it'll be a few years before I've done enough of it to want grad students to help me out.

    Anyway, I much prefer being ahead of the curve than behind it. I worked on categorification for years before that became a fashionable topic. It would have seemed like the kiss of death to work on any subject with the word "category" in it: for example, the NSF never funded anyone who called themselves a "category theorist". But now that has changed: categorification is quite fashionable, and many youngsters who got interested in that subject thanks to me seem to be doing well. (I feel like listing them, but will restrain myself.)

    I think it should be even easier to develop a branch of mathematics that concentrates on environmental issues. Of course if they are called "mathematicians", they should get jobs in math departments, and do work that's mathematically interesting. The idea would be not to compete directly with what existing climate scientists do, but instead complement it with more theoretical work — which will probably be considered "useless" and "too abstract", like most mathematics — until it turns out not to be.

    Part of my plan is to increase the overall number of scientists who have some professional (as opposed to merely hobbyist) interest in climate change, ecology, energy policy, and the like. If and when the overall ecological crisis becomes as bad as I think it will, the more scientists we have with expertise on these areas, the better off we'll be.

    By the way: I consider mathematicians to be "scientists". Vladimir Arnold said that mathematics is the branch of physics where experiments are essentially free. I think of mathematics as the branch of science that applies to all possible universes.

    However, math is influenced by scientists studying this particular universe, and it influences that science in return. Right now, for example, a lot of the most important and prestigious work on pure mathematics is heavily influenced by string theory, which of course arose from the attempt to understand elementary particles and the like. The synergy between mathematics and physics of this sort is very famous, but I wouldn't be surprised if over the course of the next century there will be more synergy between mathematics and the life sciences and earth sciences. That's why the idea that I can help build up a subject of "environmental mathematics" doesn't seem hopelessly overambitious: it seems to be going with the flow, rather than fighting against it.

    Comment Source:Nathan wrote: >Is the "Mathematical Statistics" page an appropriate place to put references to books on applied statistics? Sure, that'd be great! Thanks for the information on the &mdash; possibly not yet existent? &mdash; job opportunities for "environmental mathematicians". I will have to be a bit careful accepting new grad students when I return to Riverside 2 years from now: I don't want to take idealistic students and give them an education with no job prospects. But on the other hand, I'm just barely starting to figure out what _I_ want to do, so it'll be a few years before I've done enough of it to want grad students to help me out. Anyway, I much prefer being ahead of the curve than behind it. I worked on categorification for years before that became a fashionable topic. It would have seemed like the kiss of death to work on any subject with the word "category" in it: for example, the NSF never funded anyone who called themselves a "category theorist". But now that has changed: categorification is quite <a href = "http://www.math.sunysb.edu/categorification/">fashionable</a>, and many youngsters who got interested in that subject thanks to me seem to be doing well. (I feel like listing them, but will restrain myself.) I think it should be even easier to develop a branch of mathematics that concentrates on environmental issues. Of course if they are called "mathematicians", they should get jobs in math departments, and do work that's mathematically interesting. The idea would be not to compete directly with what existing climate scientists do, but instead complement it with more theoretical work &mdash; which will probably be considered "useless" and "too abstract", like most mathematics &mdash; until it turns out not to be. Part of my plan is to increase the overall number of scientists who have some _professional_ (as opposed to merely hobbyist) interest in climate change, ecology, energy policy, and the like. If and when the overall ecological crisis becomes as bad as I think it will, the more scientists we have with expertise on these areas, the better off we'll be. By the way: I consider mathematicians to be "scientists". Vladimir Arnold said that mathematics is the branch of physics where experiments are essentially free. I think of mathematics as the branch of science that applies to all possible universes. <img src = "http://math.ucr.edu/home/baez/emoticons/tongue.gif" alt = ""/> However, math is influenced by scientists studying this particular universe, and it influences that science in return. Right now, for example, a lot of the most important and prestigious work on pure mathematics is heavily influenced by string theory, which of course arose from the attempt to understand elementary particles and the like. The synergy between mathematics and physics of this sort is very famous, but I wouldn't be surprised if over the course of the next century there will be more synergy between mathematics and the life sciences and earth sciences. That's why the idea that I can help build up a subject of "environmental mathematics" doesn't seem hopelessly overambitious: it seems to be going with the flow, rather than fighting against it.
  • 9.

    I think there is (and will continue to be) plenty of work for mathematicians in biology. I'm not sure how much of it counts as "environmental mathematics", and most of it is applied maths, statistics, and computing. Some time ago I made a list of journals dealing with "maths in biology". It reflects my interests and is not complete. It is too long to post here together with this paragraph...

    Comment Source:I think there is (and will continue to be) plenty of work for mathematicians in biology. I'm not sure how much of it counts as "environmental mathematics", and most of it is applied maths, statistics, and computing. Some time ago I made a list of journals dealing with "maths in biology". It reflects my interests and is not complete. It is too long to post here together with this paragraph...
  • 10.

    Evolutionary Bioinformatics

    Evolutionary Bioinformatics is an international, peer-reviewed journal focusing on evolutionary bioinformatics. There is growing awareness that to understand organismal form and function, through the use of molecular, genetic, genomic, and proteomic data, due consideration must be given to an organism's evolutionary context - history constrains the path an organism is obliged to take, and leaves an indelible mark on its component parts. Evolutionary Bioinformatics publishes papers on all aspects of computational evolutionary biology and evolutionary bioinformatics. Official journal of the Bioinformatics Institute.

    Systematic Biology

    Systematic Biology is the bimonthly journal of the Society of Systematic Biologists. Papers for the journal are original contributions to the theory, principles, and methods of systematics as well as phylogeny, evolution, morphology, biogeography, paleontology, genetics, and the classification of all living things. A Points of View section offers a forum for discussion, while book reviews and announcements of general interest are also featured.

    IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)

    IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) is a scholarly archival journal published quarterly that publishes research results related to the algorithmic, mathematical, statistical, and computational methods that are central in bioinformatics and computational biology; the development and testing of effective computer programs in bioinformatics; the development and optimization of biological databases; and important biological results that are obtained from the use of these methods, programs, and databases.

    PLoS Computational Biology

    PLoS Computational Biology is an open-access, peer-reviewed journal published monthly by the Public Library of Science (PLoS) in association with the International Society for Computational Biology (ISCB). PLoS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales through the application of computational methods. www.compbiol.plosjournals.org

    Bioinformatics

    Bioinformatics, from Oxford University Press, publishes the highest quality scientific papers and review articles of interest to academic and industrial researchers. Its main focus is on new developments in genome bioinformatics and computational biology. Some articles and archives are open access.

    In silico Biology

    In silico Biology (ISB) is an international a peer-reviewed, open access journal on computational molecular biology. It focuses on biologically significant computational methods and results and aims at providing essential contribution to Systems Biology. It is issued online (Germany) & print (IOS Press, New zealand).

    BMC Bioinformatics

    BMC Bioinformatics is an open access journal publishing original peer-reviewed research articles in all aspects of computational methods used in the analysis and annotation of sequences and structures, as well as all other areas of computational biology. The journal is published by BioMed Central Ltd, UK.

    EURASIP Journal on Bioinformatics and Systems Biology

    EURASIP Journal on Bioinformatics and Systems Biology publishes research results related to signal processing and bioinformatics theories and techniques relevant to a wide area of applications into the core new disciplines of genomics, proteomics, and systems biology.

    Algorithms for Molecular Biology

    Algorithms for Molecular Biology is an open access, peer-reviewed online journal that encompasses all aspects of algorithms and software tools for molecular biology and genomics. Areas of interest include algorithms for RNA and protein structure analysis, gene prediction and genome analysis, comparative sequence analysis and alignment, phylogeny, gene expression, machine learning, and combinatorial algorithms.

    Briefings in Bioinformatics

    Briefings in Bioinformatics publishes reviews for the users of databases and analytical tools of contemporary genetics and molecular biology and provides practical help and guidance to the non-specialist.

    Journal of Theoretical Biology

    The Journal of Theoretical Biology is the leading forum for theoretical papers that give insight into biological processes. It covers a very wide range of topics and is of interest to biologists in many areas of research. Many of the papers make use of mathematics, and an effort is made to make the papers intelligible to biologists as a whole. Experimental material bearing on theory is acceptable. Comment on theoretical issues or on papers published in the journal is welcomed in the form of Letters to the Editors.

    Research Areas Include: Cell Biology and Development; Developmental Biology; Ecology; Evolution; Immunology; Infectious Diseases; Mathematical Modeling, Statistics, and Data Bases; Medical Sciences and Plant Pathology; Microbiology, Molecular Biology, and Biochemistry; Physiology.

    Journal of Mathematical Biology

    The Journal of Mathematical Biology fosters the contribution of mathematical modeling and reasoning to the understanding of biological systems and the explanation of biological phenomena. The journal also serves as a forum for the presentation of biologically inspired problems of a mathematical nature. Published papers provide biological insight as a result of mathematical analysis or identify and open up challenging new types of mathematical problems derived from biological knowledge.

    Areas of biology covered include, biofluids, cell biology, physiology, neurobiology and behaviour, development, ecology, population biology, genetics and evolution, epidemiology, immunology, molecular biology, DNA and protein structure and function, and more.

    Bulletin of Mathematical Biology

    The Bulletin of Mathematical Biology is devoted to research at the junction of computational, theoretical and experimental biology. Articles offer a combination of theory and experiment, documenting theoretical advances with clear exposition of how they further biological understanding. Its aim is to be of major interest to theorists and experimental biologists alike.

    This is the official journal of the Society for Mathematical Biology.

    Biometrics

    Published on behalf of the International Biometric Society, Biometrics emphasizes the role of statistics and mathematics in the biosciences. Its objectives are to promote and extend the use of statistical and mathematical methods in the principal disciplines of biosciences by reporting on the development and application of these methods. A centerpiece of most Biometrics articles is scientific application that sets scientific or policy objectives, motivates methods development, and demonstrates the operations of new methods. Journal of the International Biometric Society

    Mathematical Biosciences

    This leading international journal publishes research and expository papers on the formulation, analysis and solution of mathematical models in the biosciences. The journal serves both mathematicians involved in solving model equations or in reaching conclusions that are testable in the real world, and biologists who are interested in forming mathematical models of biological processes and systems.

    Comment Source:### Evolutionary Bioinformatics Evolutionary Bioinformatics is an international, peer-reviewed journal focusing on evolutionary bioinformatics. There is growing awareness that to understand organismal form and function, through the use of molecular, genetic, genomic, and proteomic data, due consideration must be given to an organism's evolutionary context - history constrains the path an organism is obliged to take, and leaves an indelible mark on its component parts. Evolutionary Bioinformatics publishes papers on all aspects of computational evolutionary biology and evolutionary bioinformatics. Official journal of the Bioinformatics Institute. ### Systematic Biology Systematic Biology is the bimonthly journal of the Society of Systematic Biologists. Papers for the journal are original contributions to the theory, principles, and methods of systematics as well as phylogeny, evolution, morphology, biogeography, paleontology, genetics, and the classification of all living things. A Points of View section offers a forum for discussion, while book reviews and announcements of general interest are also featured. ### IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) is a scholarly archival journal published quarterly that publishes research results related to the algorithmic, mathematical, statistical, and computational methods that are central in bioinformatics and computational biology; the development and testing of effective computer programs in bioinformatics; the development and optimization of biological databases; and important biological results that are obtained from the use of these methods, programs, and databases. ### PLoS Computational Biology PLoS Computational Biology is an open-access, peer-reviewed journal published monthly by the Public Library of Science (PLoS) in association with the International Society for Computational Biology (ISCB). PLoS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales through the application of computational methods. www.compbiol.plosjournals.org ### Bioinformatics Bioinformatics, from Oxford University Press, publishes the highest quality scientific papers and review articles of interest to academic and industrial researchers. Its main focus is on new developments in genome bioinformatics and computational biology. Some articles and archives are open access. ### In silico Biology In silico Biology (ISB) is an international a peer-reviewed, open access journal on computational molecular biology. It focuses on biologically significant computational methods and results and aims at providing essential contribution to Systems Biology. It is issued online (Germany) & print (IOS Press, New zealand). ### BMC Bioinformatics BMC Bioinformatics is an open access journal publishing original peer-reviewed research articles in all aspects of computational methods used in the analysis and annotation of sequences and structures, as well as all other areas of computational biology. The journal is published by BioMed Central Ltd, UK. ### EURASIP Journal on Bioinformatics and Systems Biology EURASIP Journal on Bioinformatics and Systems Biology publishes research results related to signal processing and bioinformatics theories and techniques relevant to a wide area of applications into the core new disciplines of genomics, proteomics, and systems biology. ### Algorithms for Molecular Biology Algorithms for Molecular Biology is an open access, peer-reviewed online journal that encompasses all aspects of algorithms and software tools for molecular biology and genomics. Areas of interest include algorithms for RNA and protein structure analysis, gene prediction and genome analysis, comparative sequence analysis and alignment, phylogeny, gene expression, machine learning, and combinatorial algorithms. ### Briefings in Bioinformatics Briefings in Bioinformatics publishes reviews for the users of databases and analytical tools of contemporary genetics and molecular biology and provides practical help and guidance to the non-specialist. ### Journal of Theoretical Biology The Journal of Theoretical Biology is the leading forum for theoretical papers that give insight into biological processes. It covers a very wide range of topics and is of interest to biologists in many areas of research. Many of the papers make use of mathematics, and an effort is made to make the papers intelligible to biologists as a whole. Experimental material bearing on theory is acceptable. Comment on theoretical issues or on papers published in the journal is welcomed in the form of Letters to the Editors. Research Areas Include: Cell Biology and Development; Developmental Biology; Ecology; Evolution; Immunology; Infectious Diseases; Mathematical Modeling, Statistics, and Data Bases; Medical Sciences and Plant Pathology; Microbiology, Molecular Biology, and Biochemistry; Physiology. ### Journal of Mathematical Biology The Journal of Mathematical Biology fosters the contribution of mathematical modeling and reasoning to the understanding of biological systems and the explanation of biological phenomena. The journal also serves as a forum for the presentation of biologically inspired problems of a mathematical nature. Published papers provide biological insight as a result of mathematical analysis or identify and open up challenging new types of mathematical problems derived from biological knowledge. Areas of biology covered include, biofluids, cell biology, physiology, neurobiology and behaviour, development, ecology, population biology, genetics and evolution, epidemiology, immunology, molecular biology, DNA and protein structure and function, and more. ### Bulletin of Mathematical Biology The Bulletin of Mathematical Biology is devoted to research at the junction of computational, theoretical and experimental biology. Articles offer a combination of theory and experiment, documenting theoretical advances with clear exposition of how they further biological understanding. Its aim is to be of major interest to theorists and experimental biologists alike. This is the official journal of the Society for Mathematical Biology. ### Biometrics Published on behalf of the International Biometric Society, Biometrics emphasizes the role of statistics and mathematics in the biosciences. Its objectives are to promote and extend the use of statistical and mathematical methods in the principal disciplines of biosciences by reporting on the development and application of these methods. A centerpiece of most Biometrics articles is scientific application that sets scientific or policy objectives, motivates methods development, and demonstrates the operations of new methods. Journal of the International Biometric Society ### Mathematical Biosciences This leading international journal publishes research and expository papers on the formulation, analysis and solution of mathematical models in the biosciences. The journal serves both mathematicians involved in solving model equations or in reaching conclusions that are testable in the real world, and biologists who are interested in forming mathematical models of biological processes and systems.
  • 11.

    All this stuff is fascinating, Graham! I have a really good friend named Christopher Lee who works on bioinformatics at UCLA. He's been my main window into this world so far. He's fascinated by very foundational issues related to statistics, but he manages to apply his ideas to real-world problems.

    What exactly do you work on, yourself? I'm afraid we've never been formally introduced.

    Of course I could look at your webpage, but I believe that conversation has certain pleasures that are not yet obsolete.

    Comment Source:All this stuff is fascinating, Graham! I have a really good friend named [Christopher Lee](http://thinking.bioinformatics.ucla.edu/about-2/) who works on bioinformatics at UCLA. He's been my main window into this world so far. He's fascinated by very foundational issues related to statistics, but he manages to apply his ideas to real-world problems. What exactly do you work on, yourself? I'm afraid we've never been formally introduced. Of course I could look at your webpage, but I believe that conversation has certain pleasures that are not yet obsolete.
  • 12.
    edited November 2010

    Short answer: phylogenetic analysis and macroevolution.

    Longer answer. Unlike you, I am not a great conversationalist (a fact which which has nothing to do with the internet). Unlike Tim, I have never taken the idea of a career seriously. I tend to do whatever interests me and work out the money later. I've always been self-employed. My website has a brief CV. After selling my music OCR software in 2006 and exploring various ideas for a while, I started teaching myself about bioinformatics and some more general biology, and doing my own research. I've found it fascinating, and although no-one's been paying me, I now have two articles accepted. Does that count as 'work'?

    Comment Source:Short answer: [phylogenetic analysis](http://en.wikipedia.org/wiki/Phylogenetics) and [macroevolution](http://en.wikipedia.org/wiki/Macroevolution). Longer answer. Unlike you, I am not a great conversationalist (a fact which which has nothing to do with the internet). Unlike Tim, I have never taken the idea of a career seriously. I tend to do whatever interests me and work out the money later. I've always been self-employed. My [website](http://www.indriid.com/) has a [brief CV](http://www.indriid.com/grahamjones.html). After selling my [music OCR](http://en.wikipedia.org/wiki/Music_OCR) software in 2006 and exploring various ideas for a while, I started teaching myself about bioinformatics and some more general biology, and doing my own research. I've found it fascinating, and although no-one's been paying me, I now have two articles accepted. Does that count as 'work'?
  • 13.
    edited November 2010

    Unlike Tim, I have never taken the idea of a career seriously...Does that count as 'work'?

    Sure it does, that's a really interesting CV.

    My "interest" in a career is that of the lower middle class: getting a good education and then a well paid job is the only way to avoid the "social descent" and earn a living - today I'm a little bit more relaxed, but as a teenager there was quite an amount of pressure from my social environment to pursue a certain kind of "career" :-)

    Comment Source:<blockquote> <p> Unlike Tim, I have never taken the idea of a career seriously...Does that count as 'work'? </p> </blockquote> Sure it does, that's a really interesting CV. My "interest" in a career is that of the lower middle class: getting a good education and then a well paid job is the only way to avoid the "social descent" and earn a living - today I'm a little bit more relaxed, but as a teenager there was quite an amount of pressure from my social environment to pursue a certain kind of "career" :-)
  • 14.
    edited November 2010

    Graham wrote:

    Unlike you, I am not a great conversationalist...

    Just in case we ever meet, I'll warn you that I'm not much of a conversationalist in person, except when I'm feeling reasonably comfortable and the conversation is about something I find really interesting.

    I've found it fascinating, and although no-one's been paying me, I now have two articles accepted. Does that count as 'work'?

    Sure! I just wondered what you thought about and did. It's great that you have the guts to be self-employed. I've always felt unfit for life outside the bosom of academia... I never wanted to grow up and leave school.

    I'll ask you some questions about phylogenetic analysis and evolution someday... right now I'm way behind in work on a paper with a deadline. That's why I've been relatively quiet the last few days: catching up with my "day job".

    Are you into music? Do you play the stuff, or just optically character-recognize it?

    Comment Source:Graham wrote: >Unlike you, I am not a great conversationalist... Just in case we ever meet, I'll warn you that I'm not much of a conversationalist in person, _except_ when I'm feeling reasonably comfortable and the conversation is about something I find really interesting. >I've found it fascinating, and although no-one's been paying me, I now have two articles accepted. Does that count as 'work'? Sure! I just wondered what you thought about and did. It's great that you have the guts to be self-employed. I've always felt unfit for life outside the bosom of academia... I never wanted to grow up and leave school. I'll ask you some questions about phylogenetic analysis and evolution someday... right now I'm way behind in work on a paper with a deadline. That's why I've been relatively quiet the last few days: catching up with my "day job". Are you into music? Do you play the stuff, or just optically character-recognize it?
  • 15.

    I have a flute, and sometimes I play simple tunes on it, but it is really painting (landscapes) that I enjoy among the arts. My other web site has some of my work (that word again!).

    Comment Source:I have a flute, and sometimes I play simple tunes on it, but it is really painting (landscapes) that I enjoy among the arts. My [other web site](http://gjones.name/index.html) has some of my work (that word again!).
  • 16.
    edited November 2010

    Nice paintings!

    Are these made with the help of photographs? Don't worry, Vermeer used a camera obscura and I think he's great, so I won't hold it against you if you use more modern technology.

    I do music, mainly piano improvisation and drumming but also some electronic stuff. I would love to do a combination of music and visual art, as that link hints, but I'll probably never give myself enough time to get good at it. I'm better at pure math, and climate change is more urgent, so those take precedence, even though music is more fun.

    Comment Source:<b>Nice paintings!</b> <img src = "http://math.ucr.edu/home/baez/emoticons/love.gif" alt = ""/> Are these made with the help of photographs? Don't worry, Vermeer used a _camera obscura_ and I think he's great, so I won't hold it against you if you use more modern technology. I do music, mainly piano improvisation and drumming but also some <a href = "http://math.ucr.edu/home/baez/music/">electronic stuff</a>. I would love to do a combination of music and visual art, as that link hints, but I'll probably never give myself enough time to get good at it. I'm better at pure math, and climate change is more urgent, so those take precedence, even though music is more fun. <img src = "http://math.ucr.edu/home/baez/emoticons/frown.gif" alt = ""/>
  • 17.

    I look at photos for reference, but don't incorporate them into the picture. I have no philosophical objections to using photos any which way. What I do is just what works for me, what I enjoy.

    Comment Source:I look at photos for reference, but don't incorporate them into the picture. I have no philosophical objections to using photos any which way. What I do is just what works for me, what I enjoy.
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