The genome of nerds

What makes a nerd a nerd? The stereotype is that of someone with a high intelligence, coupled with  social awkwardness and a wardrobe that may alert the fashion police. Now scientists think they may found the genomic links to these traits.

There was always a strong suspicion of a genetic component in people that are highly skilled in certain areas of engineering and sciences. Now we think that may be due to a particular type of viral infection.  We know that human endogenous retroviruses (HERVs) make up about 8% of the human genome (that’s more than our genes, really).  But what we don’t know is how they affect us, if at all. We think we do now. Specifically, a comprehensive study of human genomes from the 10,000 genome project has linked certain retroviral markers with education levels, certain vocations, and to a smaller extent, personal income. The result: programmers, engineers,  scientists (especially physicists, statisticians and mathematicians) all had specific HERV markers not found in the general populace. Some of these markers were located next to genes coding for proteins located in the frontal lobe: the brain area associated with problem-solving.

blood-blood-blood-VIRUS

Nerd carriers?

 

But even more so, the overall number of HERV markers those people  was considerably smaller: sometimes less than 4%, almost half of that of the general populace. Since HERV markers are generally associated with sexually transmitted viruses this finding led the researchers to hypothesize that the early hominid ancestors of the “nerd” populace tended to mate less than the general populace. Leading to fewer HERV markers, but somehow to a more specific selection for the “brainy” traits. This would also explain the stereotypical “bright but shy” nerd.

Really interesting study, and you can read more about it  here

 

 

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Data of thousands of ALS patients made available for analysis

This came up in my inbox. An interesting and welcome initiative, making thousands of ALS patients’ medical data available for analysis.

It doesn’t seem to have any sequence data (so not a bioinformatic database), but there are heaps of biomedical data in which to sink your statistical teeth.

Dear All,

My name is Hagit Alon and I am a scientific officer at Prize4Life Israel.

Prize4Life is a non-profit organization that is dedicated to accelerating treatments and a cure for ALS (also known as motor neuron disease or Lou Gehrig’s disease).

Prize4Life was founded by an ALS patient, Avichai Kremer, and is active in Israel and in the US.

Prize4Life developed a unique resource for bioinformatics researchers: The Pooled Resource Open-access ALS Clinical Trials (PRO-ACT) database.

This open-access database contains over 8500 records of ALS patients from past Phase II and Phase III clinical trials, spanning on average a year or more of data.

The data within PRO-ACT includes demographic data, clinical assessments, vital signs, lab (blood and urine) data, and also survival and medical history information. It is by far the largest ALS clinical trials database ever created, and is in fact one of the largest databases of clinical trial information currently available for any disease.

Data mining of the PRO-ACT is expected to lead to the identification of disease biomarkers, provide insight into the natural history of disease, as well as insights into the design and interpretation of clinical trials, each of which would bring us closer to finding a cure and treatment for ALS. The PRO-ACT database has been recently relaunched with more standardized and research ready data.

Now we finally have the data that may hold the key. The only thing missing is you. The next ALS breakthrough can be yours….

The data is available for research here

Thanks,

 

Hagit Alon | Scientific Officer

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Top 5 in Bioinformatics

I recently applied for a Moore Foundation grant in Data Science for the biological sciences. As part of the pre-application, I was asked to choose the top 5 works in data science in my field. Not so sure about data science, so I picked what I think are the most influential works in Bioinformatics, which is what my proposal was about. Anyhow, the choice was tough, and I came up with the following. The order in which I list the works is chronological, as I make no attempt to rank them. If you ask me in the comments “How could you choose X over Y?” my reply would probably be: “I didn’t”.

Dayhoff , M.O.,  Eck RV, and  Eck CM. 1972. A model of evolutionary change in proteins. Pp. 89-99 in Atlas of protein sequence and structure, vol. 5, National Biomedical Research Foundation, Washington D.C

Summary: this is the introduction of the PAM matrix, the paper that set the stage for our understanding of molecular evolution at the protein level, sequence alignment, and the BLASTing we all do. The question the asked: how can we quantify the changes between protein sequences? How can we develop a system that tells us, over time, the way proteins evolve? Dayhoff developed an elegant statistical method do so, which she named PAM, “Accepted Point Mutations”. She aligned hundreds of proteins and derived the frequency with which the different amino acids substitute each other. Dayhoff introduced a more robust version [PDF] in 1978, once the number of proteins she could use was enlarged for her to  count a large number of substitutions.

Altschul, S.F., Madden, T.L., Schaffer, A.A., Zhang, J., Zhang, Z., Miller, W. & Lipman, D.J. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25:3389-3402.

BLAST, Basic Local Alignment Search Tool is the go-to computational workhorse in molecular biology. It is the most cited paper in life sciences, so probably the most influential paper in biology today. For the uninitiated: BLAST allows you to take a sequence of protein or DNA, and quickly search for similar sequences in a database containing millions.  The search using one sequence takes seconds, or a few minutes at best. BLAST was actually introduced   in another paper in 1990. However, the heuristics developed here allowed for the gapped alignment of sequences, and for searching for sequences which are less similar, with statistical robustness. BLAST changed everything in molecular biology, and moved biology to the data-rich sciences. If ever there was a case for giving the Nobel in Physiology or Medicine to a computational person, BLAST is it.

Durbin R., Eddy S., Krogh A and Mitchison G Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids Cambridge University Press 1998

The Moore Foundation solicitation asked for “works” rather than just “research papers”. If there is anything common to all bioinformatics labs, it’s this book. An overview of the basic sequence analysis methods. This books summarizes the pre-2000 foundation upon which almost all our knowledge is currently built: pairwise alignment, Markov Models, multiple sequence alignment, profiles, PSSMs, and phylogenetics.

Gene Ontology: tool for the unification of biology. The Gene Ontology Consortium (2000) Nature Genetics 25: 25-29

Not a research paper, and not a book, but a “commentary”. This work popularized to the use of ontologies in bioinformatics and cemented GO as the main ontology we use.

Pevzner PA, Tang H, Waterman MS. An Eulerian path approach to DNA fragment assemblyProc Natl Acad Sci USA. 2001 Aug 14;98(17):9748-53.

Sequence assembly using de-Bruijn graphs, making the assembly tractable for a large number of sequences. At the time, shotgun sequences produced by by Sanger sequencing could still be assembled in a finite time solving for a Hamiltonian path . Once next-generation sequencing data started pouring in, the use of de-Bruijn graphs and a Eulerian path became essential. For a great explanation of the methodological transition see this article in Nature Biotechnology

Yes, I know there are many deserving works not in here. When boiling down to five, the choice is almost arbitrary. If you feel offended that a work you like is not here, then I’m sorry.

haters-gonna-hate_1042

 

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Support Vector Machines explained well

 

Found this on Reddit r/machinelearning

(In related news, there’s a machine learning subreddit. Wow.)

Support Vector Machines (warning: Wikipedia dense article alert in previous link!) are learning models used for classification: which individuals in a population belong where? So… how do SVM and the mysterious “kernel” work?

The user curious_thoughts asked for an explanation of SVMs like s/he was a five year old. User copperking stepped up to the plate:

We have 2 colors of balls on the table that we want to separate.

svm1

We get a stick and put it on the table, this works pretty well right?

svm2

Some villain comes and places more balls on the table, it kind of works but one of the balls is on the wrong side and there is probably a better place to put the stick now.

svm3

SVMs try to put the stick in the best possible place by having as big a gap on either side of the stick as possible.

svm4

Now when the villain returns the stick is still in a pretty good spot.

svm5

There is another trick in the SVM toolbox that is even more important. Say the villain has seen how good you are with a stick so he gives you a new challenge.

svm6

There’s no stick in the world that will let you split those balls well, so what do you do? You flip the table of course! Throwing the balls into the air. Then, with your pro ninja skills, you grab a sheet of paper and slip it between the balls.

svm7

Now, looking at the balls from where the villain is standing, they balls will look split by some curvy line.

svm8

Boring adults the call balls data, the stick a classifier, the biggest gap trick optimization, call flipping the table kernelling and the piece of paper a hyperplane.

 

 

That was copperking’s explanation.

Related: Udi Aharoni created a video visualizing a polynomial kernel:

 

And, more recently, William Noble published a paper in Nature Biotechnology. You can access an expanded version here. Thanks to Mark Gerstein for tweeting this paper.

 

Happy kernelling!

 

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Carnival of Evolution, February 2014 Edition

Wow, I haven’t posted anything in quite a while. Things are busy outside blogoland. But committing this blog to the February edition of the Carnival of Evolution just made me do it, so here goes. We’ll do this by scales, bottom up.

Molecular

Prions are the infective agents that cause transmissible spongiform encephalopathies such as Mad Cow Disease in, well, cows, and Kuru or Kreuzfeldt-Jakob disease in humans.  Apparently prions are subject to natural selection — evolution — and as the Lab Rat reports, no DNA is required.

800px-Prion_Replication

Fibril model of prion propagation. Source: wikipedia

Back to genomes, can some genomes evolve more slowly than others? Larry Moran tackles this question in Sandwalk.

Microbial

The E. coli long-term evolution experiment is an ongoing study in experimental evolution led by Richard Lenski that has been tracking genetic changes in 12 initially identical populations of asexual Escherichia coli bacteria since 24 February 1988. What have we learned? A meta-post linking to other posts summarizes five important things you can learn by looking at over 50,000 generations of bacterial evolution. Larry Moran discusses the unpredictability of evolution and potentiation in Lenski’s long-term evolution experiment.

 

800px-Lenski's_12_long-term_lines_of_E._coli_on_25_June_2008

The 12 evolving E. coli populations on June 25, 2008 Source: Wikipedia

Animal

A new book is out, The Monkey’s Voyage by Alan de Queiroz, and it is reviewed by Richard Conniff. How Did Monkeys Cross the Atlantic? A Near-Miraculous Answer was posted at strange behaviors. Speaking of monkeys, or rather apes, a comparative examination fo the chimp and human genomes reveal that 154 human genes have undergone positive selection compared with 233 chimp genes, after our phylogenetic split. Surprisingly, these are not the genes you may expect to have been selected as such.

From primates to canines, one dog has managed to outlive all others in its species… or its genes have. How? Read Carl Zimmer’s fascinating story on How A Dog Has Lived For Eleven Thousand Years posted at The Loom. In contrast, one species which is no longer with us is the Beelzebufu frog, also known as the Frog from Hell. Yes, this one ate dinosaurs, some 75 million years ago. Yikes.

As climate change continues to affect our world, species migrate and/or change phenotypes to adapt.  Or do they? Ben Haller recommends that you read Andrew Hendry’s post in Eco-Evo Evo-Eco to find out more.


Jump to 4:09 to see the Frog from Hell.

Mineral

How can you solve evolutionary problems with computers? A blog written by C. Titus Brown’s students explains evolutionary simulations and experiments in silico. While Bradly Alicea presents methods for Bet-hedging and Evolutionary Futures posted at Synthetic Daisies. A re-examination of Hamilton’s rule tells us why altruism is not only not rare as an evolutionary trait, it should probably be expected and quite frequent. Bjorn Ostman reports in Pleiotropy about Sewall Wright’s last paper on adaptive landscapes.

 

hedging-stocks-2

Bet-hedging as an investment strategy. Use a rowboat and a hang-glider.

While Titus’s students and others have been evolving things in computers, John Wilkins tackles the question whether life exists at all. No spoilers here, you will have to read it. You should probably also read Wilkins’s new book, on the Nature of Classification

 

That’s it! Thank you for being with us, a short post for a short month. Don’t forget to submit to the March carnival!

 

 

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Science funding on other planets

Got this from a tweet by Casey Bergman

 

ipN0ExT

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BOSC 2014 Guess the Keynote Competition

(From Peter Cock, via the OBF News Blog)

 

We’re pleased to officially confirm that one of the two keynote speakers
for the 15th annual Bioinformatics Open Source Conference (BOSC 2014) will
be C. Titus Brown, as he announced on Twitter recently:

Titus Brown (@ctitusbrown):
Excited to be a keynote speaker at BOSC 2014! My title:
“A History of Bioinformatics (in the year 2039)”
– plenty of room for mischief ;)
https://twitter.com/ctitusbrown/status/410934403565490176

In recognition of the growing use of Twitter and social media within science
as a way of connecting across geographical divides, we’re announcing a
Twitter competition to guess who is scheduled to give the second keynote
at BOSC 2014 in Boston.

To enter, please tweet using hashtag #bosc2014 and include us via @OBF_BOSC,
e.g.

I think @OBF_BOSC should invite “Professor X” to be a keynote speaker
at #BOSC2014 because…

The first correct entry (within one week) will be awarded one complementary
BOSC 2014 registration fee for themselves, or a nominated group member. This
does not cover travel or accommodation, and there is no cash substitute if you
cannot attend BOSC 2014. Members of the OBF board, BOSC organizing
committee, and ISMB SIG committee are not eligible, nor are the keynote
speakers themselves.

We intend to announce the mystery keynote speaker and any Twitter competition
winner in one week’s time, but reserve the right to cut short, modify, or
cancel the competition.

Our ulterior motive is to crowd source ideas for future keynote speakers in
BOSC 2015, so some serious suggestions please

Further details about BOSC 2014 will be posted here:
http://www.open-bio.org/wiki/BOSC_2014

Thank you,

Peter Cock & Nomi Harris, BOSC 2014 co-chairs.

This was also posted to the OBF News Blog,
http://news.open-bio.org/news/2013/12/bosc-2014-keynote-competition/

BOSC and the OBF are on Twitter as:
https://twitter.com/OBF_BOSC
https://twitter.com/OBF_news

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Lord of the papers

Three figures from the undergrad who is always high
Seven tables from the lab tech with his heart of stone
Nine supplements from the postdocs, with careers doomed to die
One manuscript for the Editor on his dark throne
In the journal submission form, where the shadows lie
One paper to rule them all, one paper to find them
One paper to bring them in and in the darkness bind them
In the submission form, where the shadows lie

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PhD position in Statistical Protein Structure Prediction, Copenhagen, Denmark

One of the major unsolved problems in bioinformatics is the protein folding problem: given an amino acid sequence, predict the overall three-dimensional structure of the corresponding protein. It has been known since the seminal work of Christian B. Anfinsen in the early seventies that the sequence of a protein encodes its structure, but the exact details of the encoding still remain elusive. Since the protein folding problem is of enormous practical, theoretical and medical importance – and in addition forms a fascinating intellectual challenge – it is often called the holy grail of bioinformatics.Currently, most protein structure prediction methods are based on rather ad hoc approaches. The aim of this project is to develop and implement a statistically rigorous method to predict the structure of proteins, building on various probabilistic models of protein structure developed by the Hamelryck group (see Bibliography). The method will also take the dynamic nature of proteins into account.

Bibliography:

Boomsma, W., Mardia, KV., Taylor, CC., Ferkinghoff-Borg, J., Krogh, A. and Hamelryck, T. (2008) A generative, probabilistic model of local protein structure. Proc. Natl. Acad. Sci. USA, 105, 8932-8937
Mardia, KV., Kent, JT., Zhang, Z., Taylor, C., Hamelryck, T. (2012) Mixtures of concentrated multivariate sine distributions with applications to bioinformatics. J. Appl. Stat. 39, 2475-2492.
Boomsma, W., Frellsen, J., Harder, T., Bottaro, S., Johansson, KE., Tian, P., Stovgaard, K., Andreetta, C., Olsson, S., Valentin, J., Antonov, L., Christensen, A., Borg, M., Jensen, J., Lindorff-Larsen, K., Ferkinghoff-Borg, J., Hamelryck, T. (2013) PHAISTOS: A framework for Markov chain Monte Carlo simulation and inference of protein structure. J. Comput. Chem. 34, 1697-705
Hamelryck, T., Mardia, KV., Ferkinghoff-Borg, J., Editors. (2012) Bayesian methods in structural bioinformatics. Book in the Springer series “Statistics for biology and health”, 385 pages, 13 chapters. Springer Verlag, March, 2012
Valentin, J., Andreetta, C., Boomsma, W., Bottaro, S., Ferkinghoff-Borg, J., Frellsen, J., Mardia, KV, Tian, P., Hamelryck, T. (2013) Formulation of probabilistic models of protein structure in atomic detail using the reference ratio method. Proteins. Accepted.

Requirements: Knowledge of statistics, machine learning and programming (C++ or equivalent). Knowledge of biology or biophysics is a plus but not a requirement.
Place of enrollment: Department of Biology, Bioinformatics Center
Supervisor: Assoc. Prof. Thomas Hamelryck
Co-supervisor: Prof. Michael Sørensen from Department of Mathematical Sciences

Apply here: http://dsin.ku.dk/positions/

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Your Genome, Yourself?

We have Palaeolithic emotions, medieval institutions and God-like technologies.

E.O. Wilson

 

Whole genome sequencing will soon be cheap enough to be widely affordable. We are nearing the time when omics data may be retained for patients on a wide basis. These may include full exome, haplotype, full genome sequencing, tissue level transcriptomic data, microbiome and meta-transcrimtome, metabolome… the sky, or rather personal healthcare budget, is the limit.

Personal genomic advocates today present sequencing as a personal choice. When faced with concerns such as privacy, the general response from personalized medicine advocates is that the benefits outweigh privacy concerns, and in any case the people making the choice to sequence their genomes (at least now), are making an informed personal choice. This means that whatever possible detriment that may ensue from sequencing the genome will only affect that person. So, for example, denial of life insurance due to a genomic findings (legal in many countries) will only affect the person having their genome sequenced. In the US, where healthcare is privatized, denial of health insurance due to genetics is illegal, but the application of higher premiums is a concern. For example, some health insurance providers in the US charge higher premiums if the insured has two X chromosomes,  although you usually don’t need full-genome sequencing to determine that genotype. Other privacy concerns may include the leaking (via legal or illegal means) of genomic information to various entities you may not want to have your DNA data.

Trouble is, getting your genome sequenced  is not solely a personal choice: a person’s genomic information contains that of their family as well. So by having your own ‘omic information stored, you are making a choice for your siblings, parents, and children (including those yet unborn). So you are making a choice for them to know, or at least suspect, that they have certain genotypes they may or may not wish to know about. Michael Snyder, one of the strongest advocates of personal genomics has a habit of saying: “don’t sequence your genome if you are a worrier”. You may not be, but your unborn daughter may be. You may be able to correctly interpret the probabilistic data your genome provides, but your son or brother may not.

Or they may just be a private persons who would not want their genomic information out there, even by proxy.  In realistic terms, by cross-referencing familial and genomic databases, your daughter may be denied certain health or life insurance coverage, based on a genotype an insurance company does not like: which may simply mean an over-interpretation of the limited predictive power of genomic data. By having your data accessible, some of her data are accessible as well, indirectly. No database is crack-proof, and re-identifying supposedly anonymous genomic data is surprisingly easy . Familial DNA matching, coupled with surreptitious collection of DNA is becoming common practice with law enforcement to generate suspect lists. As the availability of genomic data increases, so does the erosion of personal privacy.

This all sounds rather alarmist, counter-progressive, and may give me the appearance of a bit of a Luddite. Especially when coming from a genome scientist… What about the huge benefits that await us from personal genomics? Should privacy and unfounded (or well-founded) anxieties stand in the way of progress? My prediction: they probably won’t. As the cost of personal genomics decrease, and the benefits (currently somewhat hyped)  increase, genotyping may start to be mandated by healthcare providers, and perhaps even some employers. But revisit the motto of this post: should we not, at least, consider some of the implications of our choices upon others, if not ourselves, given our “paleolithic emotions and medieval institutions”?

 

http://blogs.cdc.gov/genomics/files/2011/08/woman_testtube2.jpg

Source: CDC (Public Domain) http://blogs.cdc.gov/genomics/2011/08/25/think-before-you-spit-do-personal-genomic-tests-improve-health/

 

 

 

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Music Monday: I’ll see you in my dreams

Because.. Django reinhardt.

 

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The Right to Read

Since this is Open Access Week, I thought I’d do the Open-Access / CC thing and share someone else’s work. In this case, a highly topical short story written by Richard Stallman.  The author also has a constantly updated page with comments on the restrictions placed today on sharing reading materials. As you will see, this story may be not too far-fetched as it first seems…

The Right to Read

The following article appeared in the February 1997 issue of Communications of the ACM (Volume 40, Number 2).

Copyright © 1996, 2002, 2007, 2009, 2010 Richard Stallman

Reproduced under CC-BY-Noderiv license

From The Road To Tycho, a collection of articles about the antecedents of the Lunarian Revolution, published in Luna City in 2096.

For Dan Halbert, the road to Tycho began in college—when Lissa Lenz asked to borrow his computer. Hers had broken down, and unless she could borrow another, she would fail her midterm project. There was no one she dared ask, except Dan.

This put Dan in a dilemma. He had to help her—but if he lent her his computer, she might read his books. Aside from the fact that you could go to prison for many years for letting someone else read your books, the very idea shocked him at first. Like everyone, he had been taught since elementary school that sharing books was nasty and wrong—something that only pirates would do.

Continue reading The Right to Read →

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The 2014 International Biocuration Conference

Hi all,
I’m happy to say that the 2014 International Biocuration Conference is off to a good start. I have attended this excellent meeting twice before, and this year I am honored to be on the organizing committee. There was a lot of work behind the scenes, and we have agreed on five session topics.  I am co-chairing the Functional Annotations session together with Paul Thomas. So please submit your talks and papers! Papers will be reviewed separately from talks for a special issue of DATABASE.
Here’s the official announcement:
The International Biocuration Conference is a unique event for curators and developers of biological databases to discuss their work, promote collaborations, and foster a sense of community in this very active and growing area of research. For the 7th International Biocuration Conference in Toronto, Canada you are invited to submit your work for publication. This call for papers is done in collaboration with DATABASE: The Journal of Biological Databases and Curation. The DATABASE journal will publish an online Virtual Issue of the accepted papers. This is a great occasion to enhance the recognition of your work and of our profession by the greater biological research communities.
This year there are five topic sessions from which submitters are invited to select:
1. Clinical Annotations
2. Systems Biology Curation
3. Functional Annotations
4. Microbial Informatics
5. Data Integration and Data Sharing
The manuscript review process will be expedited for these papers and we will thus need to be firm on the submission deadline:
- Submission deadline: November 15, 2013
- First decisions: December 6, 2013
- Deadline for revisions: January 10, 2014
- Final decisions: February 21, 2014
- Conference: April 6-9, 2014
Authors wishing to submit to DATABASE for the 2014 Biocuration Virtual issue should go to the DATABASE home page (http://database.oxfordjournals.org) and click on the “Submit Now!” after having read the “Instructions to Authors”. Authors should CLEARLY state that they are submitting this manuscript for consideration for the Biocuration 2014 conference so that the DATABASE staff will ensure appropriate fast-track for inclusion in this meeting’s proceedings. We look forward to your participation at Biocuration 2014 the 7th International Biocuration Conference.
To be considered for a Biocuration 2014 presentation you MUST register and SUBMIT an abstract for the meeting. Meeting registration will be opening up in time for the Submission deadline. The selection of oral presentations at the conference is not associated with the publication and review of the DATABASE Virtual Issue.
The proceedings of the 2013 meeting, the Biocuration 2013 Virtual Issue, are online: http://www.oxfordjournals.org/our_journals/databa/biocuration_virtual_issue.html
Kind regards,
-Biocuration 2014 Organizing Committee
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For Ada Lovelace Day: Florence Nightingale

Note: a repost of a 2010 post I published for Ada Lovelace day. Unfortunately, I am too busy these days to write a new one. “Ada Lovelace Day is celebrated today to “…raise the profile of women in science, technology, engineering and maths.”

So without further ado:

She is a ‘ministering angel’ without any exaggeration in these hospitals, and as her slender form glides quietly along each corridor, every poor fellow’s face softens with gratitude at the sight of her. When all the medical officers have retired for the night and silence and darkness have settled down upon those miles of prostrate sick, she may be observed alone, with a little lamp in her hand, making her solitary rounds

– the Times newspaper, 8 February 1855

It’s Ada Lovelace Day, and time to write about your favorite woman in science.

Florence Nightingale is best known for founding the profession of modern nursing. Today nursing is a skilled degree-earning profession, requiring extensive training, with professional rights and responsibilities. That was not the case less than 120 years ago, when normally only the military and religious orders offered semi-skilled assistance to physicians. Nightingale changed all that, and revolutionizing the way medicine is practiced. Historically known as the “Lady with the Lamp”, the angel of soldiers in the Crimean War, she ministered to the wounded not only with care and compassion, but with a newly-applied professionalism. This professional approach included keeping medical records and using them to improve health care.

Nightingale is less known for her managerial and statistical acumen, and her pivotal role in medical statistics. Nightingale kept meticulous notes of mortality rates at the Scutari hospital in Istanbul which declined dramatically during her administration. Upon her return to London, she compiled the records into a new polar diagram, known as Nightingale Rose Chart. The data is plotted by month in 30-degree wedges. Red represents deaths by injury, blue – death by disease, and black – death by other causes.

Note that this is not a pie-chart. The wedges are all in 30-degrees (so 12 wedges/months fill a circle) and the contribution of each cause of death is proportional to each wedge’s radius. Nightingale’s visualization of the role preventable diseases play in battlefield deaths made a very strong case to military authorities, Parliament and Queen Victoria to carry out her proposed hospital reforms. Specifically for adopting hospital sanitation practices and dramatically reducing death from preventable infectious diseases.

Here is an interesting critique of the Nightingale Rose Charts which is presented at Dynamic Diagrams. It appears that by placing the preventable diseases wedge-section in the outer section of the wedge, the blue received a proportionally larger area, an artifact of this radial plot. This does not detract at all from her achievements, and, as shown in the corrected charts, not even from her case for improving hospital sanitation to reduce preventable diseases as the leading cause of death, regardless of presentation format. (Pie charts are usually problematic).

You can read more about the Mathematical affiliation of Nightingale in this excerpt form the Newsletter of the Association for Women in Mathematics. One interesting factoid: she was the first woman to be nominated a fellow of the Royal Statistical Society.

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Why not use the Journal Impact Factor: a Seven Point Primer

After a series of tweets and a couple of Facebook posts about the problems of the Journal Impact Factor (JIF), I was approached by a colleague who asked me: “so why are you obsessed with this”?  My answer was that it irks me that I have to use the JIF next to my publications in so many different reports (grant reports, university annual activities, proposals, etc.)  since it is a bad metric to evaluate the merit of my papers, and as a scientist, I do not like using bad metrics.
I assume that many readers of my blog constitute the proverbial choir on which my preaching would be wasted. Specifically, those who understand what the Thomson-Reuters Journal Impact Factor is, and how became such a poorly-understood and overused and abused metric.  However, for those who have no idea what I am talking about, or for those who are thinking “what is wrong with the Impact Factor”? this post would hopefully be informative, if not valuable.  It is a brief post. There was a lot written about the JIF, and the plausible alternatives that can be used to assess journal quality and impact, and I provide a list of further reading material sources at the end. Finally, for those who, like me, think that there are many wrong things with this metric and its use, and would like to convey that information, I hopefully provide some basic arguments.

What is the Journal Impact Factor?

The JIF is supposed to be a proxy for a journal’s impact: i.e. how much influence the journal has in the scientific community. It is calculated as follows:

A = number of times that articles published in the journal in years X-1 and X-2  from this journal were cited in year X

B = number of citable items  in the journal in years X-1 and X-2

JIF(X) = A/B

Seems simple enough. The ratio  of the number of citations to the number of publications. The higher the ratio, the more the articles are being cited. Therefore, the journal’s impact is higher.

Why is the JIF a bad metric? There are several reasons.

Continue reading Why not use the Journal Impact Factor: a Seven Point Primer →
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