Tag Archives: science

Scientist spotlight: supervised and unsupervised methods for microbiome data analysis with Dr Nandita Garud 

7 Mar

I got to know Nandita Garud when she was a PhD student in the biology department at Stanford and I was a postdoc there. While we were in the same lab, we got to collaborate on two papers: one about population genetics and drug resistance evolution and one about rats in New York City. After finishing her PhD, Nandita worked at UCSF as a postdoc and then took a job as an assistant professor at UCLA. You can read more about her interesting work on the microbiome, fruit flies and other topics on her website. I asked her about a recent paper on using supervised and unsupervised methods to analyze microbiome data. 

Image: Headshot of Dr Nandita Garud, assistant professor UCLA
Headshot of Dr Nandita Garud, assistant professor UCLA

Pleuni: Hi Nandita! Thanks for taking the time to chat with me! Can you tell me in a few sentences what your job is?

Nandita: Hi Pleuni! Thank you so much for inviting me to chat about my work. I am an assistant professor in the Department of Ecology and Evolutionary Biology at UCLA. My research is on understanding the evolutionary dynamics of natural populations, currently with a focus on the human microbiome, but I also work on Drosophila and other organisms!  My research group (or, ‘lab’) consists of several PhD students that perform computational work to understand how natural populations evolve. 

Pleuni: So, you consider the community of microbes that live in my intestinal tract as a natural population, is that right? And they evolve? 

Nandita: That’s correct. I consider populations that live outside a test tube in the lab to be natural populations. Interestingly, gut microbiota can evolve on even 1-day timescales, even in the absence of a selective pressure like antibiotics!

Pleuni: I saw that you published a paper about supervised and unsupervised methods for background noise correction in human gut microbiome data. Could you explain what the human gut microbiome is? And why you need background noise correction for it?

Nandita: The human gut microbiome is a complex community that is composed of hundreds of microbial species coexisting and interacting with one another. The human microbiome is known to play an essential role in health, and changes in the microbiome are associated with numerous diseases like diabetes, obesity, and inflammatory bowel disease. Being able to predict disease status from the human microbiome is important for helping individuals diagnose any illnesses they may have. One major complication, however, is that technical variables, such as how the DNA was extracted from the sample, can introduce noise in the data, making it harder to predict human phenotypes. So, background noise correction is an important approach for addressing this data heterogeneity so that more reliable predictions can be made. 

Pleuni: Thanks! In the new paper from your lab, you compare supervised methods (which are currently standard for noise correction) and unsupervised methods (which have not been applied to microbiome data). What is the difference here between supervised and unsupervised methods?

Nandita: Supervised methods are ones where a machine is shown labeled data and is trained to understand the differences between data classes. Unsupervised methods are ones where the machine needs to figure out on its own what groupings are present in the data. We use an unsupervised approach because we don’t always know what sources of noise contribute to variation in the data. 

Pleuni: Okay, thanks! So, I imagine something like this: If microbial species A is always 2x as abundant in samples that were sequenced with machine X vs machine Y, then we can correct by changing the abundance of species A so that it matches between the two machines? Is that what’s happening? 

Nandita: Yes, but we aren’t explicitly adjusting the abundances, rather, throwing away variation due to noise. 

Pleuni: Does this mean that you do a dimension reduction method first and then throw away dimensions? 

Nandita: Exactly — we do PCA (principal component analysis) and then throw away the first PCs (principal components) because they usually are correlated with noise. We do run the risk of throwing away signal too, but that’s the tradeoff in an unsupervised approach. But when we compare this unsupervised approach to the standard supervised approaches, it can work just as well in many scenarios! And the good thing is that this way we can correct for unidentified confounders. 

Pleuni: Cool 😎 Thank you for explaining all of this, Nandita! 

I have one more question. What is something you like to do when you are not doing science? 

Nandita: I enjoy taking walks with my family and enjoying the outdoors in Los Angeles! 

Pleuni: Thank you Nandita! 

Here is a link to the paper: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009838

The website of the Garud lab: https://garud.eeb.ucla.edu/

Scientist spotlight: meet Dr Sabah Ul-Hasan!

28 Apr

Dr Ul-Hasan (they/them) is a postdoc and lecturer in bioinformatics under Dr Andrew Su and Dr Dawn Eastmond at Scripps Research, doing biocuration and automated data integration work within the Gene Wiki project of Wikidata. They received their PhD in Quantitative & Systems Biology from UC Merced, their Master’s in Biochemistry from the University of New Hampshire and their BSc degrees (3 majors! Biology, Chemistry, and Environmental & Sustainability Studies) from the University of Utah. Sabah is involved in what feels like a thousand different activities related to science, research, coding, outreach, conservation, environmental justice and other things. 

I got to know Sabah a couple of years ago when I visited UC Merced and then started following them on twitter. One thing I really love about them is how they don’t limit themselves to just doing one thing.They are ambitious and radical. They founded the Biota project to connect underrepresented communities with nature. They are a filmmaker (see here)! They volunteer for The Carpentries, and they started the venom-microbiome research consortium. They organize workshops, speak at events, teach classes and do many other things. 

In my opinion, too few scientists use their platform to fight for justice and to share their passion and knowledge. At the same time, many PhD students and postdocs and even assistant professors are shy about taking a stance, thinking that they would speak up louder (about science or justice or both) when they are more senior. But Sabah proves that you don’t have to be a tenured professor to make a difference in science (they have more than 8000 followers on twitter, just saying). 

Pleuni: Hi Sabah, thanks for taking the time to answer my questions! Could you tell us in a few sentences how you became interested in data science? 

Sabah: One of my dissertation chapters involved data that was over 100 years old. I know this isn’t a new concept for anyone doing paleo research. I was also well-familiar with “old” data through all the climate change reports that have come up in the public over the years. 

However, to directly work with data like that I realized there were so many more questions I wanted to ask people from 100 years ago. That then got me wondering, “How can I contribute to research in a way that can be sustainable 20, 50, or even 5 years from now?”. 

My interest in data science thus came from a position of wanting to be part of something bigger in terms of the infrastructure for how we can sustain the science of today and tomorrow. 

Pleuni: How did you start learning coding skills? Was it hard for you to learn? 

Sabah: I was first introduced to R during my (Biochemistry) Master’s at the University of New Hampshire in 2013. I sat-in on a casual meeting among graduate students and postdocs and truly had no idea what anyone was talking about. 

The data analysis section of my MSc thesis ended up utilizing Excel to make bar charts. In retrospect, I see how much faster I could’ve done the analyses if I took the time to learn coding. When I began the doctoral program at UC Merced in January 2015, I knew coding was a skill I wanted to learn and so I did through classes and workshops. 

Now it’s my job as a postdoctoral scholar and lecturer for bioinformatics, and I still sometimes struggle with basic concepts. The difference between then and now is I’m a lot better at admitting when I don’t know something, how to ask a question for what I need to learn, and where to go to find that answer. 

I’m not sure anyone who does bioinformatics considers themselves an expert, but perhaps the expertise lies within the ability to problem solve especially when it is difficult or can feel overwhelming. In sum, the sooner you can confront your fears the better! Don’t let them freeze you. Believe in your ability to constantly learn and grow, even when you’re a titled expert!

Pleuni: For your paper that appeared in Plos One in 2019, you studied the diversity of microorganisms (including archaea, bacteria and eukaryotes) in seawater and sediment in three different locations. It sounds like a complex dataset to work with. 

Community ecology across bacteria, archaea and microbial eukaryotes in the sediment and seawater of coastal Puerto Nuevo, Baja California

Sabah: It’s funny to only be two years out from that publication and already think of so many things I would’ve done differently. I guess that’s growth! 

I attribute a lot of credit and thanks to the co-authors of the paper and those in the acknowledgements. It came a long way from when I first drafted it to the final publication form, and posting it on bioRxiv also helped a great deal in soliciting feedback. 

What I think really makes a difference is the transparency of that research and associated code, especially in reference to data clean-up (which is the bulk of the analysis work, in personal opinion). I’ve since received several inquiries from people for their own work and to me that feels great to know that it can serve as something people can apply to their own research in making things a little easier. 

I also think it’s important we as scientists specify the microbes we’re investigating in any ‘microbial community’ -type paper. Many of the amplicon and metagenomics studies I see really focus on bacteria or fungi, which is absolutely fine but that isn’t a comprehensive microbial community for what many of the titles for these papers tend to imply. In this study, too, we focus on whatever microbial groups we identified solely through 16S and 18S. We need to be better at saying what the data is rather than wordsmithing for a nice story. That will help the next group build upon those gaps for something stronger next time, and overall our intent as scientists is to always have research be advancing further and further. Right? 

Pleuni: You used R for your data analysis (but also other software such as QIIME2). What do you like or not like about R? Could you imagine doing a paper like this one without R?

Sabah: Using wrappers such as QIIME2 and mothur are great for people who want to do an analysis of a microbial dataset and then perhaps never touch one again. For me, I found myself continuously asking a lot of “Why?” and wanting to dig deeper on the fundamentals behind what the software I was using. In the end, R took more time to learn short-term but made more sense to me of what was happening each step of the way in the analysis. It was also a good way to affirm my results in trying different avenues and seeing the same output. 

What I learned from putting together the paper is it’s not about finding the ‘right’ or ‘wrong’ answer, it’s about finding an answer that is logical and as unbiased as possible. A lot of the time we have these hypotheses we ‘prove’ through confirmation bias. To me, code (when done with intention) is a way to step outside of ourselves and see what the data is telling us rather than what we want the data to say — and that’s where the interesting science lives.

This publication, for example, wasn’t exactly what we were wanting to see. It’s actually a failed attempt at sequencing the venom microbial community of Californiconus californicus, which was the focus of my dissertation (venom microbiomes), due to too much host contamination of the tissues we sampled for that region of Puerto Nuevo. So, what do we do? Do we call it all a wash? There was a lot of thought, time, and resources that went into that work. 

I had sampled the sediment and water of the area, along with some generic chemistry tests, to see if the venom microbial community was largely specialized to the snail venom glands or from the surrounding environment (they burrow in the sand). That data was still usable, had good replication, and we didn’t know anything about the microbial community of Puerto Nuevo before that point. Ah-ha! A different story than we were thinking, but still a valuable one. Let the data tell you, don’t misconstrue the data to fit your narrative. 

R, and all the programming languages I’ve learned thus far, have helped me learn that.

Pleuni: On your twitter profile, you list many interests, such as advocacy, consulting, data visualization. Can you tell us a bit about your different interests? Are these things linked to each other?

Sabah: Well… haha. The link is that, at heart, I’m a bit of a troublemaker. It’s the nature of a scientist to ask a lot of questions, and asking too many questions can often get us into trouble! I likewise enjoy being asked a lot of questions, and hope to always maintain humility in learning just as much from high school students as I do from tenured professors. 

I wanted my Twitter profile and bio to emulate that duality of being both a ‘credible academic’ while also pushing back on what we define as ‘the norm’. I disagree with the idea that a science expert needs to possess a PhD (or some other form of higher education certification) because of the privilege and whiteness involved, but I do also benefit from it after completing the process and there is of course also danger in believing ‘just anyone’ on the internet. And I love learning and helping, which are really the only drivers behind all my many interests.

In my view, the most important quality in being a scientist is being approachable. If only a few people can understand the work you do, then what’s the point? That’s why I’m on Twitter, and also as a way to keep myself grounded, especially learning from moments of being called out (which does happen from time to time). I’d also say my family keeps me in check, as I’m one of the few with a science background. I have one cousin on my Mom’s side with a Ph.D. and that’s it for our extended family of over 100 people (South Asian families are big). Being a good scientist is just as much about humanity as it is about the basic research. I think only good things can come from staying tuned into the reality of the world around us, even though it can feel like a lot to balance.

Pleuni: Do you have any advice for the bio and chem Master’s students in my Data Science class? 

Sabah: My advice is to just go for it! 

This past Fall I taught a bioinformatics course to (mainly) graduate students and it was an adventure for all of us. It was my first time as a full instructor for a course (versus a teaching assistant), during COVID no less, and it was also the first time many students in the course were getting into bioinformatics. 

At the end, it was clear to me that student progress in the course wasn’t about who knew how much at the start but rather about showing up with enthusiasm and simply trying. That went both ways for me as the instructor giving lectures my all as well as for the students and their performance. And life happens! I had to cancel one of the days due to personal life things, and that’s okay. Be good to yourself when you need to and also don’t hold yourself back. And be good to others, too. We really never know what someone else may be experiencing behind the scenes for them to be flakey or on edge, and the more we can find the good in each other the better we can focus on doing the good science. 

On that note, I can’t express enough how much of a difference it’s made in my life to work for or alongside with even just one considerate person. As they say, “You are what you eat.”. My PhD co-advisors (Dr Tanja Woyke and Dr Clarissa Nobile) and my current PIs (Dr Su and Dr Eastmond) are truly outstanding people. They have so many stresses in their own careers and lives, and they still somehow show up with kindness and professionalism every day. And they also believe in me to do good work, even when I’ve had a bad week (or month!). That trust really goes such a long way when you’re underrepresented in your field, and often used to being discouraged and/or people expecting very little of you. Being entrusted to teach a course at a renowned research institute directly out of my PhD, for instance, is a big reason why I chose this position in knowing that my voice was heard and respected. That’s been true throughout, and makes it much easier to show up with my best foot forward even on the tough days.

Tying it all together, so many times I’ve got myself stuck because I see others who are ahead of me, doing better than me, and/or with access to more resources than me. One truth we can all agree upon is that life is unfair, and while hopefully it will become equitable over time through our own efforts to create change the fact is that life is still happening in the meantime. No one will help you as much as you can help yourself, and the moments where I’ve been able to just sit down and see something through is how I’ve realized more and more just how much more ability I have than I thought. You’re much more capable than you give yourself credit! It’s super cheesy, but it’s very true. And feel free to reach out any time!

Pleuni: Thanks for answering my questions, Sabah! So much here that resonates with me, including one of the last things you said, that you realized that you have more ability than you thought. This happens to me too! As just one example, just over a year ago, I didn’t think I could learn Machine Learning, but now I am even teaching it. Not that I am suddenly an expert, but I can do it and it is no longer scary. 

I look forward to seeing all the science, art, and justice-related projects you will be doing in the future! 


Sabah Ul-Hasan Google Scholar profile 

Sabah Ul-Hasan, PhD Twitter Profile (@sabahzero)

New video about how SARS-CoV2 spreads

28 Mar


I worked with Brandon Ugbunu, Senay Yitbarek and Olivia Pham to make this video about how the SARS-CoV2 virus, which causes COVID19 spreads.

Hope it’s useful!


New video: COVID19 in numbers: R0, the case fatality rate and why we need to flatten the curve

11 Mar


Pleuni Pennings, Senay Yitbarek and Brandon Ogbunu are asking all mayor and presidents to help reduce R0 for the SARS-CoV2 / COVID19 outbreak by canceling events and washing your hands.

Brandon Ogbunu (Brown University),  Senay Yitbarek (UC Berkeley) and I (Pleuni Pennings, SFSU) made a video about the two numbers most often used to describe the new coronavirus outbreak: R0 and the case fatality rate. We also talk about why we should and how we can “flatten the curve.”

Feel free to share, use as homework assignment, show in the classroom! Ideal for college level biology and calculus classes.


Translations kindly contributed by the following people:

Dutch translation by Alex Verkade.
Spanish translation by Berenice Chavez and Cecilia Hernandez.
Portuguese translation by Murillo Rodrigues and Luiza Ostrowski.

The video is also on YouTube: https://youtu.be/-3xZVhFhP8w

Download the slides here: COVID19_FlatteningTheCurveSlidesMarch172020

Meet Simone Webb, Bioinformatics and Immunology PhD student

2 Dec


I am spotlighting scientists who code for my students who are learning to code in Python. Today, I’ve chatted with Simone Webb from the UK. Simone Webb is a PhD student in the group of Professor Haniffa at Newcastle University in the UK.

Pleuni: Hi Simone, how did you get into coding?

Simone: I got into coding during my undergraduate degree, where I took some compulsory statistics and intro to bioinformatics courses.

To be honest, I struggled with it a lot! These courses remain my worst grades during university. However, there was something about it that drew me to it. The maths-based logic of it all really appealed to me at a time where the bio-related content I was learning seemed a lot more uncertain and up for debate. I’m not a natural at it by any means.

I liked how it felt to get an answer correct during our tutorials and stuck with it.

By the time I got to my undergraduate thesis, I realized that my real interest lay in microbiology and bioinformatics. The projects on offer for my thesis didn’t have massive diversity in these fields, so I crossed my fingers and applied for the project led by our first-year bioinformatics tutor – I got in! From then onwards, it’s fair to say that I would always choose coding over wet lab work. My thesis project was purely bioinformatics and I had a very encouraging and hands-on supervisor who was patient with me and taught me a lot to do with coding technique, method and reasoning. After I graduated I knew I wanted to keep coding, whether in research or a non-academic role.

Pleuni: What is your current job or project?

Simone: I’m currently studying for a PhD in bioinformatics and immunology. I now use coding (in both R and python languages) to analyze sequencing data. In this work, code is able to help us understand exactly what cells are present in both healthy and disease tissue, and helps us look further into the role these cells could be playing.

Pleuni: Do you have any advice for students who are starting to learn coding skills?

Simone: If you have an interest in anything bioinformatics related, my advice is to seek out a role model and be brave – ask for their advice and see what you can learn from their experiences! Also, there are active online communities for women in STEM, women who code and people who are Black in academia. Reach out if any of these groups relate to you and know that you are not alone

You can find Simone on twitter under her twitter handle @SimSci9 !

Thoughts on the first Women in Computational Biology conference

15 Nov

Earlier this week I went to the first Women in Computational Biology conference at Janelia Research Campus. When I got the invite, I said yes immediately, but then I had some doubts. I wondered: why have a conference just for women? And then I worried: would it be only Ivy-league trained white women? Would this conference actually contribute to diversity in our field?

Now the conference has happened and I am back in SF, so I thought I share some thoughts.

1. While the conference was not just Ivy-league trained white women, it was still fairly white and certain groups were clearly underrepresented (e.g., Black and Latina women).

2. The conference was super interesting! I learned about image analysis, cancer genomics and machine learning. I met some great scientists. It got me excited to try new things.

3. If I were in neurobiology or image analysis, I would seriously consider applying for a job at Janelia. It is luxurious and beautiful and they have great food and amazing staff.

4. I very much enjoyed being at a women-only conference. One reason is that normally at conferences, I spend time and energy worrying that the guys in the room will be the only ones asking questions. No worries here! Or, I worry about the guys at the dinner table dominating the conversations. No worries here! Then, when a guy is giving a talk and clearly not giving proper credit to his postdocs, I wonder whether I should say something about it. At many conferences, I worry a lot, and most of that worry was absent at this conference. In addition, it was nice to feel safe to talk about women stuff. Our dinner conversation went from breast pumps to programming languages without skipping a beat. SO COOL! Being part of the majority for once is nice.

5. Being at this conference, and enjoying the safety of being surrounded by women, makes me even more motivated to help create safe spaces for my students and colleagues of color. I already make an effort to send my students to conferences for minority scientists such as SACNAS and ABRCMS. But I also want to try (again) to organize a meeting for people of color in evolutionary biology. Evolutionary biology is still a very white field with a racist history (eugenics). I think it’d be a good idea to organize a regular conference for people of color in our field. A few years ago, I applied for money to do this, but I was not successful. I will try again!

All in all, I think the conference was worth my time and a great way to meet other women in computational biology. IMG_0603


The acknowledgement section of our NSF proposal

25 Aug

A few weeks ago two colleagues and I submitted an NSF proposal. We submitted on a Friday afternoon even though the deadline wasn’t until Tuesday! I am proud that we managed this almost without any deadline stress!

I had fun and we wrote a great proposal

I know that we may not end up getting funded by NSF, but until we get that message, I plan to be very optimistic. We wrote a really neat proposal for a great project. I can’t wait to get started! The ambitious goal of the project is to determine the fitness cost of every possible point mutation in the HIV genome in vivo.

I think nobody likes to write proposals when the success rate is only 5%, but I actually enjoyed working on this proposal and I learned a lot while writing it: both about the biology of our project and about the art of proposal writing. It’s important for me to commit that to paper (OK, screen) so that if NSF decides not to fund us, I will remember that writing the proposal was actually a good experience.

Writing with a newborn

In addition the many scientists and administrators who contributed to the proposal, I also want to mention how I could write a proposal with a newborn. We started working on the proposal two weeks before I gave birth and we submitted the proposal when our baby was just shy of seven weeks old. The hours that I spent on the proposal were made possible by my mom who flew in to help and by the fact that Facebook gives new parents four months paid paternity leave so that my husband was also at home during my maternity leave. It was fun to be home together with my husband and we took shifts working and taking care of Maya. Most days I worked on the proposal just two or three hours, so a large part of the work was done by others.


Me in my home office with baby, changing table, a laptop and a grant writing handbook.

It was a huge team effort

Many people were involved in writing the proposal. Many more than I ever expected to be. I want to list them here so that I remember who helped out and also to show that being a researcher doesn’t have to be a lonely affair.

Note that these people are only the people I am aware off. Others certainly helped my co-PI Adi Stern.

The main team that wrote the proposal consisted of four people:

  • co-PI Adi Stern (Tel Aviv)
  • postdoc Marion Hartl (SFSU)
  • professional grant writer Kristin Harper
  • myself

At SFSU, people from the Office for Research and Sponsored Programs helped:

  • Rowena Manalo
  • Raman Paul
  • Michael Scott
  • Jessica Mankus
  • Uschi Simonis (vice-dean for Research)

At Stanford there were

  • co-PI Bob Shafer
  • collaborator David Katzenstein
  • Elizabeth White (Katzenstein lab)
  • Holly Osborne (Office for Sponsored Research)

In Tel Aviv

  • Office for Sponsored Research
  • Adi Stern’s lab members brainstormed ideas
  • Maoz Gelbart help with ideas and figures

Colleagues who read earlier versions of the proposal

  • Sarah Cobey (U Chicago)
  • Sarah Cohen (SFSU)
  • Alison Feder (Stanford)
  • Nandita Garud (UCSF)
  • Arbel Harpak (Stanford)
  • Joachim Hermisson (U Vienna)
  • Claus Wilke (U Texas Austin)

A huge thank you to all these amazing people! I am lucky to be part of such a supportive community.


Five Reasons why you should attend the Annual SACNAS National Conference

27 Apr

Guest post by: Bridget Hansen, SFSU undergraduate researcher


First, who am I? What is SACNAS?

My name is Bridget Hansen and I am an undergraduate in Microbiology at San Francisco State University, doing research at the Romberg Tiburon Center for Environmental Studies. Over the summer, I participated in the Howard Hughes Medical Institute Excellent Research Opportunity Program (HHMI-ExROP) summer research and the AMGEN program at the University of California, Berkeley. I worked on a project that I then presented at the SACNAS Conference this past October.

SACNAS stands for the Society for Advancing Chicanos/Hispanics and Native Americans in Science. This society, made up of many successful Chicanos and Native Americans in science related careers, puts on a national conference once a year. The conference has opportunities for scientists at all levels, from undergraduates to professors and researchers. Many graduate school recruiters and other professional organizations come to this conference to recruit, providing a great platform for networking.

I used this opportunity to network for graduate schools! I will be attending a PhD program in the fall, in part, thanks to my interactions that I had at SACNAS.

What happens at the SACNAS National Conference?

Students from all over the country submit abstracts for the opportunity to present their work, either in the form of a poster or an oral presentation. The students had a scheduled time and room to present. Other than presentations, the meat of the conference was geared towards guest speakers and networking. The whole goal of the conference was to introduce young students to the world of research and science related careers! The best part is the graduate student recruiter booths where you have the opportunity to chat with recruiters, professors, and students from that university.

Five reasons why I recommend SACNAS

  1. The networking

There were hundreds of booths set up, all stocked with professors, recruiters, graduate students and pamphlets listing the reasons why you should come to their school. Nearly every research institution was in attendance, looking for the next round of graduate students to apply to their programs. They want you to apply to their programs but most importantly, they want to make sure their school lines up with your research interests. You can ask them about the programs, the application process, what it is like to live in that part of the United States and any funding opportunities. Exchanging business cards or information is very common and the badge that you are given upon arriving even has a scanner square that the recruiters can use to keep in touch with you (they scan your badge and your e-mail is logged with them).

I spoke to over a dozen booths about their programs and had all my questions answered. I was even recruited during my poster session presentation! Which brings me to my next point.

  1. The presentations

The presentations are great for two reasons: 1. You have an opportunity to talk about your work and receive feedback on your presentation skills and 2. Other schools can come by your presentation and see you as a researcher. This is fantastic! I am not the best on paper in some ways, so having other schools approach me based on my science, reassures me that I am more than just my GPA or my GRE scores. Not only that, I received written evaluations based on my presentation skills and my poster, which were all constructive and positive!

  1. The seminars

The guest speakers focus on their journeys as minorities in the sciences and how their transforming experiences have brought them to where they are today. They inspire us to continue to pursue our passions and create a sense of community, which I will get to in a minute. The seminars are also great opportunities for junior scientists, like myself, because they offer an opportunity to check out new areas of research, hear about different paths in science outside of academia and get insights into how to be successful. There are workshops on how to give a compelling interview, what to expect in graduate school and how to master networking. All of these skills are important ones that give you a competitive edge.

  1. The experience

The experience itself was wonderful. Surrounded by 3,600 other students, mentors and researchers, the conference felt grand. I say grand because the conference center was massive, the sheer number of attendees was at times, a bit overwhelming, and the hotel that we were assigned to left me in awe. The Gaylord National Conference Center in Washington D.C. was an incredible place to hold this conference this year. As apart of the conference fees, we were fed in a large hall, which also created a sense of community.

  1. The sense of community

The SACNAS conference creates a sense of community for young scientists; a community that they can be a part of throughout their careers in the sciences. The idea of having a supportive community that I can be part of is a great feeling, especially coming from a background that does not have any college graduates. It can be lonely sometimes, walking into a completely new field that no one you grew up around, has any experience in. So, when I attended the conference with other San Francisco State students who were also presenting, they immediately considered me one of the group, even though we had just met. Similarly, other students from other places also welcomed conversation with open arms. The inclusion that occurs at SACNAS is excellent.

Overall, I highly recommend attending a SACNAS national conference. It looks great on your CV, it is great for your future scientific career and definitely gives you an edge when applying for graduate school. Bring your own business cards!

If you have any questions about SACNAS, please refer to the SACNAS website: http://sacnas.org .

Hope to see you there next year! I will be attending as a graduate student!

Feel free to contact me with questions at: blhansen “at” mail.sfsu.edu or missbridgette4 “at” aol.com. and indicate you read this blog so I know where the questions are coming from!



Some recommended and not-recommended science-related books

6 Jan

Last year I read some really cool books that are somehow related to my work. I also read books that were so annoying, I didn’t even finish them. I wanted to share some of my thoughts here.

Jim Ottaviani, Maris Wicks: Primates

Lovely comic book about three women researchers who study primates (Jane Goodall, Dian Fossey, and Biruté Galdikas). Great gift idea! Link to book


Steven Strogatz, The joy of X.

Highly recommended! Great book with essays about fun math. Made me want to learn more. Link to book.

Jennine Capó Crucet: Make Your Home Among Strangers

I very much enjoyed this novel about a young cuban woman who is the first of her family to go to college. It’s an easy read, but it has some insights that may be useful for those of us who teach. Link to book.

Vanessa Woods: Bonobo handshake

Well written memoire by traveler, writer and bonobo researcher Woods, with a lot of background on Congo and neighboring countries. The descriptions of awful violence during the wars in Congo may be upsetting to some. Link to book.

Bill Nye: Undeniable

The topic of this book, evolution, is dear to my heart, but I didn’t manage to finish it. It is simply not well written / edited. Link to book

Frank Ryan: Virolution

This book was definitely worse than Bill Nye’s book! It is not well written and it is full of nonsense about evolution. Disappointing, because it would have been nice to have a good popular book on viruses and evolution. Here Carl Zimmer explains why the book is not recommended: link to book review.





How a collaboration on imperfect drug penetration got started

3 Feb

Almost three years ago, in early 2012, I attended a talk by Martin Nowak. He talked about cancer and one of the things he said was that treatment with multiple drugs at the same time is a good idea because it helps prevent the evolution of drug resistance. Specifically, he explained, when treatment is with multiple drugs, the pathogen (tumor cells in the case of cancer) needs to acquire multiple resistance mutations at the same time in order to escape drug pressure.

As I listened to Martin Nowak’s talk, I was thinking of HIV, not cancer. At that time, I had already spent about two years working on drug resistance in HIV. Treatment of HIV is always with multiple drugs, for the same reason that Martin Nowak highlighted in his talk: it helps prevent the evolution of drug resistance.

However, as I read the HIV drug resistance literature and analyzed sequence data from HIV patients, I found evidence that drug resistance mutations in HIV tend to accumulate one at a time. This is contrary to the generally accepted idea that the pathogen must acquire resistance mutations simultaneously.

There seemed to be a clear mismatch between data and theory. Data show mutations are acquired one at a time, and theory says mutations must be acquired simultaneously. One of the two must be wrong, and it can’t be the data![1]


After Martin Nowak’s talk, I went up to him and told him how I thought data didn’t fit the theory. Martin’s response: “Oh, that is interesting!” (Imagine this being said with an Austrian accent). “Let’s meet and talk about it.”

So, we met. Logically, Alison Hill and Daniel Rosenbloom, then grad students in Martin’s group, were there too. I had already met with Alison and Daniel many times, since they were also working on drug resistance in HIV.  John Wakeley (my advisor at Harvard) came to the meeting too.

Between the five of us, we brainstormed and fairly quickly realized that one solution to the conundrum was to assume that a body’s patient consisted of different compartments and that each drug may not penetrate into each compartment. Maybe we found this solution quickly because Alison and Daniel had already been thinking of the issue of drug penetration in the context of another project. A body compartment that has only one drug instead of two or three would allow a pathogen that has acquired one drug resistance mutation to replicate. If a pathogen with just one mutation has a place to replicate, this makes it possible for the pathogen to acquire resistance mutations one at a time.

We decided to start a collaboration to analyze a formal model to see whether our intuition was correct. Over the following three years, there were some personnel changes and several moves, graduations and new jobs. Stefany Moreno joined the project as a student from the European MEME Master’s program when she spent a semester in Martin’s group. When I moved to Stanford, Dmitri Petrov became involved in the project. Next, Alison and Daniel each got their PhD and started postdocs (Alison at Harvard, Daniel at Columbia), Stefany got her MSc and started a PhD in Groningen, I had a baby and became an assistant professor at SFSU. No one would have been surprised if the project would never have been finished! But we stuck with it and after many hours of work, especially by the first authors Alison and Stefany, and uncountable Google Hangout meetings, we can now confidently say that our initial intuition from that meeting in 2012 was correct. Compartments with imperfect drug penetration indeed allow pathogens to acquire drug resistance one mutation at a time. And, importantly, the evolution of multi-drug resistance can happen fast if mutations can be acquired one at a time, much faster than when simultaneous mutations are needed.

Our manuscript can be found on the BioRxiv (link). It is entitled “Imperfect drug penetration leads to spatial monotherapy and rapid evolution of multi-drug resistance.” We hope you find it useful!

[1]Of course, it could be my interpretation of the data!

Stefany Moreno (in large window), Alison Hill, Daniel Rosenbloom and myself in one of the many Google Hangout meetings we had.

Stefany Moreno (in large window), Alison Hill, Daniel Rosenbloom and myself in one of the many Google Hangout meetings we had.