There is really not much to say other than to point everyone to this article: Bacteria on Russian ‘sex satellite’ survive reentry | Science | The Guardian
It defininely wins the strangest microbial headline of the month. The article restates some of the silly claims about how what they are finding supports panspermia .. but ignore the article and just enjoy the headline.
Postdoctoral Position in Microbial Ecology and Evolution
Jessica Green at the University of Oregon Green (http://pages.uoregon.edu/green/) is currently seeking a postdoctoral researcher to explore fundamental questions in microbial ecology and evolution. Applicants should have a PhD in a biological, computational, mathematical, or statistical field with extensive training using theory and/or modeling to understand the ecology and evolution of complex biological communities, and strong writing skills. Experience developing and applying quantitative phylogenetic ecological methods is highly desirable, but not explicitly required for candidates who have otherwise demonstrated strong quantitative skills.
The successful candidate will play a key role in the Seagrass Microbiome Project (http://seagrassmicrobiome.org) in collaboration among Jonathan Eisen https://phylogenomics.wordpress.com), Jay Stachowicz http://www-eve.ucdavis.edu/stachowicz/stachowicz.shtml, and Jenna Lang (http://jennomics.com/) at the University of California, Davis. The Seagrass Microbiome Project aims to integrate the long interest in seagrass ecology and ecosystem science with more recent work on microbiomes to produce a deeper, more mechanistic understanding of the ecology and evolution of seagrasses and the ecosystems on which they depend. Our studies of the community of microorganisms that live in and on seagrasses – the seagrass “microbiome” – will contribute to a broader understanding of host-microbe systems biology, and will benefit from ongoing University of Oregon research programs including the Microbial Ecology and Theory of Animals Center for Systems Biology (http://meta.uoregon.edu/) and the Biology and Built Environment Center (http://biobe.uoregon.edu/).
The position is available for 1 year with the possibility for renewal depending on performance. The start date is flexible. Please email questions regarding the position to Jessica Green (jlgreen).
To apply
A complete application will consist of the following materials:
(1) a brief cover letter explaining your background and career interests
(2) CV (including publications)
(3) names and contact information for three references
Submit materials to ie2jobs. Subject: Posting 14431
To ensure consideration, please submit applications by November 1, 2014, but the position will remain open until filled.
Women and minorities encouraged to apply. We invite applications from qualified candidates who share our commitment to diversity.
The University of Oregon is an equal opportunity, affirmative action institution committed to cultural diversity and compliance with the ADA. The University encourages all qualified individuals to apply, and does not discriminate on the basis of any protected status, including veteran and disability status.
POSTDOC ON HORIZONTAL GENE TRANSFER AND GENOME EVOLUTION
An NSF-funded
postdoctoral position is available to work on a collaborative project between the labs of Dr. Jeff Palmer (Department of Biology, Indiana University, Bloomington) and Dr. Claude dePamphilis (Department of Biology, Penn State University, University Park). This project is a follow-up to papers on the mitochondrial and nuclear genomes of the basal angiosperm Amborella that were led by our labs and published in the Dec. 20, 2013 issue of Science. The project focuses on evolutionary gene transfer, including transfer of mitochondrial and plastid sequences to the nucleus of Amborella, and the extensive horizontal transfer of foreign mitochondrial sequences to the mitochondrion of Amborella.
This
is a strictly bioinformatic/comparative genomic project involving extensive analysis of genome-scale sequence data. A Ph.D. in computational biology, evolutionary genetics, or a related field is required, and proficiency in computer programming is expected. Competitive candidates will have a strong record of prior publication in genome-scale data analysis, including bioinformatic pipeline construction, phylogenomics, and/or genome evolution. This position is funded for two years, with continued appointment dependent upon availability of funding. Salary will be commensurate with experience, and full benefits are included.
To apply,
please submit, as a single unified PDF, a cover letter detailing research interests and experience, a C.V., and contact information for three professional references to jpalmer) or Claude dePamphilis (cwd3).
Indiana University
is an equal employment and affirmative action employer and a provider of ADA services. All
qualified applicants will receive consideration for employment without regard to age, ethnicity, color, race, religion, sex, sexual orientation or identity, national origin, disability status, or protected veteran status.
Postdoc on HGT & genome evolution in plants – Jeff Palmer & Claude dePamphilis.docx
Well, this is disappointing, to say the least – there is a conference coming up in July 2015 on “Forecasting Evolution”: SFB 680 | Molecular Basis of Evolutionary Innovations at the Gulbenkian Foundation in Lisbon.
Here is the listed lineup of invited speakers:
For a whopping 20:1 ratio of men to women or 4.8% women. And this in a field that is just overflowing with excellent female researchers.
So I dug around a little bit. Here is another meeting from the same group at the University of Cologne – a group known as SFB 680. SFB 680: Molecular Ecology and Evolution: Cologne Spring Meeting 2012.
Speakers:
Session and Meeting Chairs:
That would be 25:5 or 16.6% female.
And then there was this: Perspectives in Biophysics in October 2014.
For a 19:3 ratio or 13.6 % women for the speakers and if you include session chairs it comes to 23:5 or 18 % female total.
And Evolutionary Innovations in 2010.
Invited speakers:
For a whopping ratio of 27:1 or 3.6 %
The only meeting from them I could find with a decent / non massively skewed ratio was the following very small one: Evolution of Development
———————————————
See this page for other posts of mine on this and related topics.
Over at Nothing In Biology Makes Sense! I wrote about a recent paper that analyzed the biogeography of skin microbiota. If you’re interested in your body as a conglomerate of unique ecosystems and want to know more – go check out “What’s lurking on your glabella“.
Data Rights & Data Wrongs
A workshop organized by
Innovating Communication in Scholarship (ICIS)
University of California, Davis
Date & Time: December 10, 2014 from 9:00 am – 5:00 pm
Location: MPR, Student Community Center, UC Davis
Register: https://www.eventbrite.com/e/data-rights-data-wrongs-tickets-14079810091
Full Agenda: http://icis.ucdavis.edu/?page_id=329
Keynote talks:
Dr. Christine Borgman, Professor & Presidential Chair, iSchool, UCLA
John Wilbanks, Chief Commons Officer, Sage Bionetworks
Scholars are increasingly subject to pressures from funding bodies, disciplinary norms, professional and personal ethics, and institutional directives to share their research data and make it available for reuse. There is, however, a great deal of heterogeneity across the research enterprise with respect to what is meant by ‘data’ and ‘data sharing,’ why data sharing is deemed important, and what data management strategies are considered most effective. Moreover, data are often difficult and costly to produce and share. Therefore, many scholars view these as a significant product of their intellectual labor for which they should receive some sort of credit towards tenure and promotion, authorial recognition through citation, or financial compensation. While balancing all of these considerations is desirable to promote increased access to data, it is difficult to guarantee that the concerns of all research stakeholders will be met given (1) the diverse forms that data can take, as well as the mobility and malleability of data given widespread access to new information technologies, (2) the complex and variable legal status of data as not-quite/not-always property, and (3) the ethical considerations and legal restrictions implicated in the sharing and reuse of data related to sensitive topics such as personal health information, national security, and vulnerable populations. This workshop will address theoretical concerns and pragmatic solutions that can be harnessed to help researchers comply with requirements or desires to share their data in ways they deem appropriate for their goals.
OK. It is Halloween night and I am tired and need to get my kids to sleep. But someone on Twitter just pointed me to an opinion piece just out in the New York Times: Academic Science Isn’t Sexist – NYTimes.com and after reading it I felt I had to write a quick post.
The opinion piece is by Wendy M. Williams and Stephen J. Ceci and discusses work by them (and coauthors). In particular they discuss findings in a massive report “Women in Academic Science: A Changing Landscape” by Stephen J. Ceci, Donna K. Ginther, Shulamit Kahn, and Wendy M. Williams in Psychological Science in the Public Interest. I note – kudos to the authors for making this available freely and under what may be an open license and also apparently for making much of their data available behind their analyses.
The opinion piece and the associated article have a ton of things to discuss and ponder and analyze for anyone interested in the general issue of women in academic science. I am not in any position at this time to comment on any of the specific claims made by the authors on this topic. But certainly I have a ton of reading to do and am looking forward to it.
However, I do want to write about one thing – really just one single thing – that really bothers me about their New York Times article. I do not know if this was intentional on their part, but regardless I think there is a major flaw in their piece.
First, to set the stage — their article starts off with the following sentences:
Academic science has a gender problem: specifically, the almost daily reports about hostile workplaces, low pay, delayed promotion and even physical aggression against women. Particularly in math-intensive fields like the physical sciences, computer science and engineering, women make up only 25 to 30 percent of junior faculty, and 7 to 15 percent of senior faculty, leading many to claim that the inhospitable work environment is to blame.
This then sets the stage for the authors to discuss their analyses which leads them to conclude that in recent times, there are not biases against women in hiring, publishing, tenure, and other areas. Again, I am not in any position to examine or dispute their claims about these analyses – to either support them or refute them.
But the piece makes what to me appears to be a dangerous and unsupported connection. They lump together what one could call “career progression” topics (such as pay, promotion, publishing, citation, etc) with workplace topics (hostility and physical aggression against women). And yet, they only present or discuss data on the career progression issues. Yet once they claim to find that career progression for women in math heavy fields seems to be going well recently, they imply that the other workplace issues must not be a problem. This is seen in statements like “While no career is without setbacks and challenges” and “As we found, when the evidence of mistreatment goes beyond the anecdotal” and “leading many to claim that the inhospitable work environment is to blame.”
Whether one agrees with any or all of their analyses (which again, I am not addressing here) I see no justification for their inclusion of any mention of hostile workplaces and physical agression against women. So – does this mean that a woman who does well in her career cannot experience physical aggression of any kind? Also – I note – I am unclear I guess in some of their terminology usage – is their use of the term “physical aggression” here meant to discount reports of sexual violence? This reminds me of the “Why I stayed” stories of domestic violence. Just because a women’s career is doing OK does not mean that she did not experience workplace hostility or physical or sexual violence. I hope – I truly hope – that the authors did not intend to imply this. But whether they did or not, their logic appears to be both flawed and offensive.
UPDATE 1. November 1, 8:30 AM
Building a Storify about this.
UPDATE 2: Nov 3, 2014. Some other posts also criticizing the NY Times piece
Well, this is pretty deranged: Soylent CEO Is Lifehacking Water By Pissing In the Sink. Forget all the wackiness of Soylent and the idea of limiting water intake. And just look at the part of this on the micro biome
Feces are almost entirely deceased gut bacteria and water. I massacred my gut bacteria the day before by consuming a DIY Soylent version with no fiber and taking 500mg of Rifaximin, an antibiotic with poor bioavailability, meaning it stays in your gut and kills bacteria. Soylent’s microbiome consultant advised that this is a terrible idea so I do not recommend it. However, it worked. Throughout the challenge I did not defecate.
So – he took Rifaximin to kill his gut microbiome because he thought that would help him not defecate. And then because he did not defecate he concluded that the Rifaximin played some role in such anti-defecation? OMFG. This is both bad science and some, well, crazy a*s-sh*t. I – I – I – I just do not know what else to say.
Hat tip to Andrea Kuszewski.
I found myself writing this email to some collaborators, but halfway through realized that it’d be nice to get EVERYBODY’s input. Probably, one of you is going to review my next paper, so how awesome would it be for you to just tell me what you think now, and make both of our lives easier later.
To test whether taxa vary significantly across groups of samples, we first need to filter the OTU table to get rid of OTUs that are not present in most of the samples and/or that do not vary across samples. This must happen for statistical reasons.
As far as I know, there are two ways to do this. One, is to remove OTUs that occur in fewer than 25% of the samples (25% is suggested by the QIIME folks). The other is to calculate the variance of the OTUs across samples and remove the OTUs that have a variance less than 0.00001 (0.00001 is an arbitrary number thrown out there by the phyloseq developer.)
A third option would be to apply both criteria.
My inclination would be to go with the third option, but mostly because I want to limit as much as possible the number of hypothesis tests that we do in order to avoid draconian p-value corrections.
I’m not a big fan of arbitrary thresholds, but they are so frequently required that I’ve made my peace with them. However, if someone can suggest a non-arbitrary threshold, that’d be great.
But mostly, I want to make sure that everyone agrees now on the method that we use so that I only have to do this once. Thoughts?
Jonathan Eisen's Lab 