There are a few useful but often underutilised Python 3 syntactic tricks that I have picked up over the last few years; I have chosen to continue in the spirit of Mark and share them here.
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A new way of eating too much
Fresh off the pages of Therapeutic Advances in Endocrinology and Metabolism comes a warning no self-respecting sweet tooth should ignore.
“Liquorice is not just a candy,” write a team of ten from Chicago. “Life-threatening complications can occur with excess use.” Hold on to your teabags. Liquorice – the Marmite of sweets – is about to become a lot more sinister.
Continue readingTwo Tools for Systematically Compiling Ensembles of Protein Structures
In order to know how a protein works, we generally want to know its 3-dimensional structure. We then can either try to solve it ourselves (which requires considerable time, skill, and resources), or look for it in the Protein Data Bank, in case it has already been solved. The vast majority of structures in the Protein Data Bank (PDB) are solved through protein crystallography, and represent a “snapshot” of the conformational space available to our protein of interest. Continue reading
Which fragment first?
Crystallographic fragment based lead discovery is a now a routine technique, which can sample 1000’s of compounds per week. But how do we identify the most appropriate compounds to screen against our target of interest?
Continue readingAIRR community meeting
Hi everyone,
Today is the day for another blog post from me. Last month I attended an AIRR conference in Genoa, Italy (https://www.antibodysociety.org/airrc/meetings/communityiv/). It was the fourth AIRR conference, and I was nice to see lots of field-leading people participating. Compared to the last AIRR meeting almost 2 years ago, the agenda of the conference was dominated by machine learning and big data topics. In my short blog post, I will discuss two talks that covered these two exciting topics.
Continue readingWhat is the hydrophobic-polar (HP) model?
Proteins are fascinating. They are ubiquitous in living organisms, carrying out all kinds of functions: from structural support to unbelievably powerful catalysis. And yet, despite their ubiquity, we are still bemused by their functioning, not to mention by how they came to be. As computational scientists, our research at OPIG is mostly about modelling proteins in different forms. We are a very heterogeneous group that leverages approaches of diverse scale: from modelling proteins as nodes in a complex interaction network, to full atomistic models that help us understand how they behave.
Continue readingExciting new studies in OAS
Hi everyone!
Today is the day for another blog post from me. Here, I would like to give you an update on new studies, which were deposited in the Observed Antibody Space (OAS) resource and take a closer look at one of these studies. To date, we have curated 57 studies in OAS, where we provide raw nucleotide and numbered amino acid sequences for download. These amino acid sequences have been filtered using ANARCI parsing, which ensures that the sequences align to respective species HMM profiles and do not have unusual indels and frameshifts. More than 660 million numbered amino acid sequences are deposited in OAS, where every sequence keeps a link to its corresponding nucleotide sequence. Recently we added two more studies to OAS: Sheng et al., (2017) and Setliff et al., (2018). We numbered roughly 2.8 and 46 million sequences in Sheng et al., and Setliff et al., studies respectively. In this blog post, I would like to talk more about the uniqueness of Setliff et al., data.
OPunting 2018
Hi everyone!
Today is the day to present to you my belated blogpost on OPIG punting (or OPunting for short). I promise I was not procrastinating on writing it. I am currently not in Oxford, as I am visiting beautiful Zurich as proved by the photo below. Continue reading
The Curious Case Of A Human Chimera
In my role as a PhD student in the OPIG group, I integrate and analyse data from various biological, chemical and data sources. As I am interested in the intersection between chemistry, biology and daily life, it seems suitable that my next BLOPIG posts will discuss and highlight how biological phenomena have either influenced law or history.
Connection between Law and Biology – The Curious Case Of A Human Chimera
Our scene opens in a dark lab, where a scientist injects himself with an unknown substance. The voice over notes that they created a monster named “Chimera” while searching for their hero “Bellerophon”. This scene is the famous opening scene of the movie “Mission Impossible II” , where we are introduced to the dangerous bioweapon “Chimera”, a combination of multiple diseases. As “Chimera” is a mythological beast from Ancient Greek mythology, with a lion’s head, a goat’s body, and a serpent’s tail, the naming of this bioweapon seems appropriate.
What does this dangerous mixture of multiple diseases, an ancient mythological monster and the promised connection between law and biology have in common?
Apart from a really bad joke, the term “Chimera” is an actual term in biology to describe a biological entity of multiple diverse components, e.g. a human organism, whose cells are composed of distinct genotypes.
In case of tetragametic chimerism, human chimeras thus possess forty-six chromosome pairs instead of the “usual” set of twenty-six chromosome pairs, and as such, their organs and tissues are constructed according to the DNA outlined in the respective organ or tissue.
Tetragametic chimerism occurs by the fertilization of two ova by two spermatozoa, which develop into zygotes. These zygotes then subsequently fuse into one organism, which continues to develop into an organism with two sets of DNA.1-2
But how did such a biological phenomenon like a chimera enter the court of law?
The Romans famously defined that the mother of a child is the one who gives birth to it (Mater sempre certa est, which can be translated as “The mother is always certain”). I would like to point out that in the times of in-vitro fertilization, this principle is no longer viable, since a child can now have both a genetic mother and a birth mother.3
This Principle was disproved in 2002, when Lydia Fairchild applied to receive Welfare for her two children and her third, unborn child, from the US State. Paternity tests were conducted on all children to prove her ex-partner’s paternity. While the tests proved the paternity of the father without a doubt, Lydia was shown to be no genetic match to her children.
Accused of being a “wellfare fraud” or a surrogate, the judge ordered that Lydia Fairchild had to give birth to her third child in front of witnesses. Immediately blood samples were taken, which revealed that Lydia Fairchild also did not share DNA with this child, despite giving birth to it. Now accused of being a surrogate, Lydia’s case looked dire.
Fortunately, Lydia’s lawyer read a journal article about a similar case involving a woman named Kareen Keegan.2, 4-5 Karen, a 52-year old woman, had renal failure. As she needed a kidney replacement, Karen’s sons underwent the histocompability process to test for donation.Yet the genetic tests showed that only one of her three sons was related to her.1 Material from her entire body was tested for genetic matches to her sons’ DNA, but only genetic material of her thyroid matched her sons.2
Ultimately, the researchers concluded that Karen was a tetragametic chimera, born of the fusion of her zygote and her twin sibling in her mother’s womb. As Dr. Lynne Uhl, a pathologist and doctor of transfusion medicine at Beth Israel Deaconess Medical Center in Boston, said:
“In her blood, she was one person, but in other tissues, she had evidence of being a fusion of two individuals.”6
Subsequently, scientists collected Lydia’s cell material from various body parts and tested for a genetic match with her children. The DNA from her cervical smear was found to be a match, while the DNA collected from her skin and hair was not. Additionally, DNA samples from Lydia’s mother matched her childrens’ DNA. 4-5
Interestingly, while both Lydia and Karen were carrying two sets of DNA as a result of prenatal fusions with their twins, they didn’t show any phenotypic sign of being a chimera, e.g. different skin types or the so-called Blaschko lines.7-8
- https://www.scientificamerican.com/article/3-human-chimeras-that-already-exist/
- To, E. & Report, C. LEADING TO IDENTIFICATION OF TETRAGAMETIC CHIMERISM. 346, (2002).
- https://en.wikipedia.org/wiki/Mater_semper_certa_est
- https://pictorial.jezebel.com/one-person-two-sets-of-dna-the-strange-case-of-the-hu-1689290862
- https://web.archive.org/web/20140301211020/http://www.essentialbaby.com.au/life-style/nutrition-and-wellbeing/when-your-unborn-twin-is-your-childrens-mother-20140203-31woi.html
- http://abcnews.go.com/Primetime/shes-twin/story?id=2315693
- https://jamanetwork.com/journals/jamadermatology/fullarticle/419529
- http://biologicalexceptions.blogspot.co.uk/2015/09/when-youre-not-just-yourself.html
All links were last viewed on the 24.04.2018.
My next blog post: Can a mismatch in maternal DNA threaten a government? How Biology can Influence History.
I just wanted TensorFlow
Finally got TensorFlow to install on my Mac. You’d be tempted to think, “Jin, it’s just a pip install, surely?”
No, MacOS begs to differ! You see, if you’re on a slightly older macOS version like I was (10.12), then you’d still be using TLS 1.0 – long story short, when querying PyPI via pip to get any packages on TLS 1.0, your requests will get rejected. And this cutoff was chosen something like a week ago – SAD! If you have MacOS 10.13 and onward, TLS should be set to 1.2 so you need not worry.
TL;DR:
- Get a new version of pip (10.0); see Stack Overflow post.
- Install any dependencies for pip as necessary by doing tons of source compilations.
- Install desired package(s) as necessary.