Get ready for some excitement. International Maths Olympiad of this year was held in Chiang Mai, Thailand. You can download the problems from here, but the solutions are not posted yet. Check how many you can solve before they show up online.
This year, US team became the winner after a long hiatus of 21 years. Please note that IMO is held as an individual contest, whereas the team results are based on adding up the scores of six individual contestants from each national team. Here are the top 10 countries for this year.
United States of America
People’s Republic of China
Republic of Korea
Democratic People’s Republic of Korea
Islamic Republic of Iran
In other years, the top place is held by China, but they missed that spot this time. I was doing some analysis of scores to find where USA and China differed. Interestingly, very few members of the Chinese team solved Problem 3, but did unusually well with the most difficult problem (Problem 6). Members of Russia, which is usually another top country, stumbled with Problem 5. I spent couple of hours solving Problem 5 and it appears fairly easy to me. Someone please send me the solutions of other five to save me from spoiling the rest of the week.
The real champion of this IMO is Canadian Zhuo Qun (Alex) Song, who got a perfect score. Here are his record from the last six contests.
In the thread on valuation of Oxford Nanopore, reader George spiggot commented –
Samanta, that’s now how valuations work. If they sold 5000 sequencers, and people used 2 flow cells a month, that’s 5-10 Million a month, or 60-70M per year. Then you have price earnings ratio, have a look at Illuminas. Their value is many times earnings. In fact today, based on a 1% earnings miss they lost 3x ONTs value. ILMN make about $1B per year, but are worth 33Bn. Why is that. Investors are not paid back from revenue, it’s not a pay day loan. As for pacbio, their value is low, and stays low, because it hard to see how their revenue can scale. With ONT you can see how it scales, and moves into new markets.
George, thank you for the comment, because it is perfect time to discuss valuation these days. As you noticed, Illumina’s market valuation got whacked by over $2B for no apparent good reason. Why?
Please do not consider the following discussion as financial advice, but here is how valuation works.
There is one and only one way to properly value a business.
1. You first figure out what you can earn risk-free for your money. That answer is 3% at present.
2. Then you determine what the business returns as dividend. Is it sufficiently more than 3% after considering various risks? There are all kinds of risks in running a business, ranging from simple hacker attack (e.g. Ashley Madison) to explosions in chemistry lab, Chinese stock market crash and FDA not liking your business plan. A person investing in a business needs to account for all those risks and factor in sufficient premium over 3%. Investing in a more risky business requires higher premium.
Question: Tech companies do not pay dividend and reinvest profits in growth. Are they valued at zero?
If you do not get any dividend, you may substitute the profit margin of a rapidly growing company as dividend provided you have sufficient expectation of getting the money returned to you as dividend in future. Also remember that this act of substitution adds another risk factor, because a bird in hand is worth two in bush. For all you know, the CEO may ultimately hike his salary and leave with the profit.
At opposite pole from honest valuation sits ‘Ponzi valuation’ or ‘get rich quick’ valuation. It is based on how fast one can get rich by passing the hot potato to the next wannabe genius. No other explanation needed.
Ponzi valuation relies on myth-building. You see an abundance of visionaries trying to predict the rosy future and justify the high stock prices at the peak of a boom. They mock anyone not agreeing with them as ‘inexperienced’.
When a person with money meets a person with experience, the person with the experience winds up with the money and the person with the money winds up with the experience.
Ponzi valuations rule under two conditions – (i) high debt, (ii) large amount of opium in the market. People playing with other people’s money (OPM), such as managers of mutual/pension funds, compare companies against companies rather than looking at absolute return. That is because no pension/mutual fund manager lost job by following what the others are doing, but many were fired for trying to be safe. It is even better for their careers, when they can borrow to increase leverage and short-term performance.
Please note that our use of ‘Ponzi’ comes from Hyman Minsky (check Minsky’s financial instability hypothesis).
Which valuation is right?
Rather than right or wrong, the more pertinent question would be ‘which valuation is risky’? Risky behavior may sometimes appear exciting, and people get carried away without properly accounting for the underlying risks.
In the context of ONT, your comment makes two assumptions justifying the $1.5B valuation – (i) ILMN’s valuation, (ii) ONT is as good as ILMN. How valid are those assumptions?
i) Current valuation of ILMN – The market valuation of ILMN, based on which you justified the other numbers, appears to be mostly Ponzi valuation. There had been huge pent up demand for sequencing in 2009-2012 giving an impression of exponential growth. As of 2015, sequencing is not the biggest bottleneck, but bioinformatics is. Even within bioinformatics, the first level of hurdle (storage and preliminary analysis of large amount of data) is not the largest constraint. Now the question is how to make biologically/medically relevant discoveries from that data, given that many of the low-hanging fruits are gone. That difficult task requires more than sequencing.
ii) ‘Too much sequencing’ factor – Let’s assume that ONT becomes as successful as ILMN. In that case, the saturating demand for more sequencing will be satisfied by ILMN, Pacbio, ONT and BGI with their new instrument, just to mention a few. They will eat each others margin and reduce the current ‘70%’ profit margin of ILMN.
iii) How good is ONT? – Speaking of ONT itself, I have been watching them for years and they always under-delivered, whereas the scientists surrounding them (e.g. Mick Watson, Birney) hyped up the prospects without giving a true picture of reality. Jared Simpson is the only brain around there and his work on E. coli assembly from HMM of electrical signals is commendable. However, I do not see Mick Watson’s ‘prediction’ of human genome assembly from ONT this year from that success in E. coli.
Hyping up by distorting numbers creates obstacles for anyone trying to design efficient programs. Take the example of characterization of errors. Those numbers are very important for designing any bioinformatics program, and in case of Pacbio, Mark Chaisson and Glenn Tesler wrote a fantastic first paper providing an accurate description of error profile. When it comes to ONT data, I am completely lost. Are the errors random or do they have positional bias? Do the errors have AT/GC bias, homopolymer bias? What is the relative distribution of substitutions and indels?
iv) Factors not under control for ONT – Irrespective of ONT’s performance, what will happen, if ILMN market cap falls to 2-3x revenue due to stock market correction? Will ONT be able to raise more funds? If ONT cannot raise money, it will have to survive on its revenue/profit and burning of existing cash. That appears to be another big and unaccounted risk factor going forward that is not currently taken into consideration.
How about stock market valuation?
Stock market valuation goes from ‘honest valuation’ at the bottom of a bust to ‘Ponzi valuation’ at the peak of a boom. That is essentially what Minsky described in his instability hypothesis. Moreover, you can also play this rule in reverse and count the number of visionaries predicting rosy future to figure out where in the business cycle we currently are.
Here is a good example full cycle of Ponzi–>honest valuation.
Sycamore Networks: From $45 Billion to Zilch
By SCOTT THURM and BEN FOX RUBIN
Updated Feb. 1, 2013 5:38 p.m. ET
There was a time when Sycamore Networks Inc. was the next big thing—a leader in the race to direct digital traffic across the Internet.
This is not that time. On Friday, Sycamore all but went out of business. The Chelmsford, Mass., company said it had completed the sale of its remaining product line and that its shareholders had voted to dissolve the company. Sycamore ended the day with a market value of about $66 million, a humbling end for a company that in March 2000 was worth nearly $45 billion.
Twitter is buzzing with a photo posted by @san_kaido –
They are deformed daisies near Fukushima, but is the deformation caused by radiation? Fasciation is the alternate explanation.
Fasciation (or cresting) is a relatively rare condition of abnormal growth in vascular plants in which the apical meristem (growing tip), which normally is concentrated around a single point and produces approximately cylindrical tissue, instead becomes elongated perpendicularly to the direction of growth, thus, producing flattened, ribbon-like, crested, or elaborately contorted tissue. Fasciation may also cause plant parts to increase in weight and volume in some instances. The phenomenon may occur in the stem, root, fruit, or flower head. Some plants are grown and prized aesthetically for their development of fasciation. Any occurrence of fasciation has several possible causes, including hormonal, genetic, bacterial, fungal, viral and environmental causes.
The answer is not either/or, because fasciation can also be caused by genetic mutation from radiation. Speaking of radiation, readers may also find the following post from 2012 relevant –
Severe Abnormalities Found in Fukushima Butterflies
It appears that the chemists at Oxford Nanopore are as competent as their bioinformaticians. On July 8th, BBC reported that three people were injured in a “violent chemical reaction” at the company. The violent chemical reaction, as it turns out, happened due to mixing of nitric acid and alcohol, which is a complete no-no for any chemistry procedure (also see this) except by those working for ISIS. Thankfully all injured employees have been discharged from the hospital.
Readers can find additional details here –
Update: Three people injured after chemical incident closes parts of Oxford Science Park
Oxford Science Park chemical incident – three injured
In other news, the company raised $109M and sports a valuation of $1.55B (GBP 1B) !! Pacbio, their closest competitor, is valued at only $399M at today’s closing price.
IP Group Says Oxford Nanopore Raises GBP70 Million In Funding Round
LONDON (Alliance News) – FTSE 250-listed intellectual property company IP Group PLC on Tuesday said its Oxford Nanopore Technologies Ltd portfolio company has raised GBP70 million in a new financing round.
Oxford Nanopore is an Oxford University spin-out focused on nanopore-based electronic molecular analysis systems.
Following the completion of the financing found, which attracted existing and new investors in the UK, US and Europe, IP Group’s undiluted stake of 19.9% in Oxford Nanopore is now valued at GBP192.9 million, representing an unrealised fair value gain for IP Group on its investment of GBP50.3 million.
IP invested another GBP13.9 million in Oxford Nanopore in the latest funding round.
It is quite ironic that one of the organizations funding Oxford Nanopore is also named ISIS Innovation, but we do not see any connection with the middle eastern group of same name or ‘violent chemical reactions’.
What is the future of this company? Clearly, every round of extra financing acts like death spiral, because the company needs to back it up with that much revenue to support its valuation. For example, a $750M valuation would require them to sell 750K individual sequencers at $1K price (assuming revenue parity for valuation in lieu of discounted cash flow). With $1.5B valuation, that expectation goes up to 1.5M sequencers. The other possibility is to sell big machines instead of isolated sequencers, but that takes away the distinguishing factor for the company.
Another troubling aspect is that even with this much funding, the company seems to have outsourced its bioinformatics to the public funding sources (e.g. Mick Watson: “we have an active grant to develop poRe, software we are writing to help scientists access and use MinION sequence data”). Will public funding be used to support various informatics requests from 750K or 1.5M different users?
P. S. Several readers asked me about Mick Watson’s hilarious ‘4 predictions about nanopore sequencing in the next 12 months’. Human genome? Hahaha !! Wake me up, when someone assembles a previously unassembled fungal or bacterial genome using ONT sequencing only. Also, his stressing of “all of the above will be possible without seeing a single A, G, C, or T (i.e. it will all be possible without base-calling the data)” seems to suggest that he does not believe Ewan Birney’s claim about 92% accuracy of ONT sequences at the nucleotide level. Neither do we, because Birney is a proven liar exposed by Dan Graur.
If there is one area of evolutionary biology benefiting greatly from high-throughput sequencing, that is the study of ‘primitive’ or ‘lower’ animals. The animals like sponges were traditionally avoided in the era of model organisms, because what can one really learn about humans based on brainless, heartless and limbless ‘simple’ animals? Surprisingly, high-throughput sequencing found those animals not to be as simple as previously thought. It is also worth pointing out the roles of two researchers (Sally Leys and Casey Dunn), who are truly pushing the boundaries by taking advantage of new sequencing techniques and asking interesting questions.
Six major steps in animal evolution: are we derived sponge larvae?
The importance of sponges and choanoflagellates in understanding evolution were highlighted in a 2009 review paper by Claud Nielsen of Natural History Museum of Denmark. Dr. Nielsen was the past president of International Society for Invertebrate Morphology, winner of Linnean Medal and the author of widely cited book ‘Animal Evolution: Interrelationships of the Living Phyla’. In the paper he wrote –
A review of the old and new literature on animal morphology/embryology and molecular studies has led me to the following scenario for the early evolution of the metazoans. The metazoan ancestor, “choanoblastaea,” was a pelagic sphere consisting of choanocytes. The evolution of multicellularity enabled division of labor between cells, and an “advanced choanoblastaea” consisted of choanocytes and nonfeeding cells. Polarity became established, and an adult, sessile stage developed. Choanocytes of the upper side became arranged in a groove with the cilia pumping water along the groove. Cells overarched the groove so that a choanocyte chamber was formed, establishing the body plan of an adult sponge; the pelagic larval stage was retained but became lecithotrophic. The sponges radiated into monophyletic Silicea, Calcarea, and Homoscleromorpha. Homoscleromorph larvae show cell layers resembling true, sealed epithelia. A homoscleromorph-like larva developed an archenteron, and the sealed epithelium made extracellular digestion possible in this isolated space. This larva became sexually mature, and the adult sponge-stage was abandoned in an extreme progenesis. This eumetazoan ancestor, “gastraea,” corresponds to Haeckel’s gastraea. Trichoplax represents this stage, but with the blastopore spread out so that the endoderm has become the underside of the creeping animal. Another lineage developed a nervous system; this “neurogastraea” is the ancestor of the Neuralia. Cnidarians have retained this organization, whereas the Triploblastica (Ctenophora+Bilateria), have developed the mesoderm. The bilaterians developed bilaterality in a primitive form in the Acoelomorpha and in an advanced form with tubular gut and long Hox cluster in the Eubilateria (Protostomia+Deuterostomia).
It is indicated that the major evolutionary steps are the result of suites of existing genes becoming co-opted into new networks that specify new structures.
The evolution of the eumetazoan ancestor from a progenetic homoscleromorph larva implies that we, as well as all the other eumetazoans, are derived sponge larvae.
The hidden biology of sponges and ctenophores
In a review paper published in Trends in Ecology and Evolution, Casey Dunn, Sally Leys and Steven Haddock went a step further and challenged the notion of human-centric understanding of animals like sponges and ctenophores. The concept of ‘hidden biology’ is explained in Fig 1 of their paper and is shown below along with the extended caption (Box 1).
All living animals belong to one of five clades: Porifera, Ctenophora, Placozoa, Cnidaria, and Bilateria. To a first approximation, the study of zoology is the study of Bilateria. Humans and all the best-studied model animal species (mouse, Drosophila melanogaster, Caenorhabditis elegans, and others) are within Bilateria. All of the terrestrial animals, and most freshwater animals that humans regularly encounter are within Bilateria. Most known animal species are within Bilateria (in fact, most known species belong to a single bilaterian clade: Arthropoda). However, if we want to understand the full breadth of animal diversity and the earliest events in animal evolution, we need to study all animals, not just Bilateria.
To a large extent, the focus on the study of bilaterians is a resource allocation decisions: zoologists spend more time and money studying bilaterians than they do nonbilaterians because they comprise most living animal species, including ourselves and the animals we are most familiar with. However, this creates a problem: currently, we see most nonbilaterian biology through the filter of bilaterian biology (Figure I). All animal clades have a mix of unique traits and traits that are shared with other animals (Figure IA). It is easier to confirm previously known traits and functions than it is to describe new traits and functions, and most previous studies have been on bilaterians. In addition, many widely used tools and reagents have been optimized for Bilateria. This makes it easier to study the aspects of nonbilaterian biology that are similar to bilaterian biology (Figure IB, gray), than it is to study traits that are only found outside Bilateria (Figure IB, black). The candidate gene approach is a widespread example of this. However, just because it is easiest to study the subset of nonbilaterian biology that is shared with bilaterians does not mean that nonbilaterians only have a subset of bilaterian biology, or that bilaterians are more advanced than other animals. It just means that many of their unique features are currently unknown to us: a ‘hidden biology’ (Figure I) that we have only the first glimpses of. This hidden biology includes novel structures and functions, facilitated by novel mechanisms, that are not found in bilaterian model species. It also includes novel mechanisms that underlie shared structures and functions. The problems of hidden biology also extend to nonmodel bilaterians, although it is more severe in nonbilaterians.
What do we miss by letting so much nonbilaterian biology stay hidden? At best, we miss out on some interesting biology, including unique morphology, developmental mechanisms, and physiology. At worst, we are systematically misled. Unfortunately, this is the case when it comes to understanding early animal evolution. It is tempting to mistake our biased perspective (Figure IB) for the actual distribution of traits (Figure IA), which gives the false impressions that nonbilaterians have only a subset of the traits found in Bilateria and, therefore, that they are ‘lower’ or ‘simpler’. This in turn plays into the misconception that living animal diversity conforms to a linear aristotelian scala naturae, from lower to higher animals, and that animal evolution has proceeded by a step-wise accumulation of complex traits, such that the more distantly an animal is related to Bilateria, the more closely it resembles the most recent common ancestor of all animals. In reality, all living animal lineages have had the same amount of time to evolve since the most recent common ancestor of all animals, and all have gain and lost multiple traits. We need to understand the traits present in all animal groups, not just those that are present in Bilateria, if we are to understand early animal evolution.
Sally Leys – Elements of a ‘nervous system’ in sponges
The claims of complexity of sponges, jellies and ctenophores do not appear far-fetched, if you go carefully through the papers of Dr. Sally Leys. For years, she collaborated with George O. Mackie and showed that jellyfish had central neural circuitry (check 2004 review ‘Central Neural Circuitry in the Jellyfish Aglantha’) and then moved her attention to sponges. Her work combines traditional electrical measurements and high-throughput sequencing. In the paper – ‘Evolutionary origins of sensation in metazoans: functional evidence for a new sensory organ in sponges’, she and co-authors showed that sponges have sensory cilium.
One of the hallmarks of multicellular organisms is the ability of their cells to trigger responses to the environment in a coordinated manner. In recent years primary cilia have been shown to be present as ‘antennae’ on almost all animal cells, and are involved in cell-to-cell signaling in development and tissue homeostasis; how this sophisticated sensory system arose has been little-studied and its evolution is key to understanding how sensation arose in the Animal Kingdom. Sponges (Porifera), one of the earliest evolving phyla, lack conventional muscles and nerves and yet sense and respond to changes in their fluid environment. Here we demonstrate the presence of non-motile cilia in sponges and studied their role as flow sensors.
Demosponges excrete wastes from their body with a stereotypic series of whole-body contractions using a structure called the osculum to regulate the water-flow through the body. In this study we show that short cilia line the inner epithelium of the sponge osculum. Ultrastructure of the cilia shows an absence of a central pair of microtubules and high speed imaging shows they are non-motile, suggesting they are not involved in generating flow. In other animals non-motile, ‘primary’, cilia are involved in sensation. Here we show that molecules known to block cationic ion channels in primary cilia and which inhibit sensory function in other organisms reduce or eliminate sponge contractions. Removal of the cilia using chloral hydrate, or removal of the whole osculum, also stops the contractions; in all instances the effect is reversible, suggesting that the cilia are involved in sensation. An analysis of sponge transcriptomes shows the presence of several transient receptor potential (TRP) channels including PKD channels known to be involved in sensing changes in flow in other animals. Together these data suggest that cilia in sponge oscula are involved in flow sensation and coordination of simple behaviour.
This is the first evidence of arrays of non-motile cilia in sponge oscula. Our findings provide support for the hypothesis that the cilia are sensory, and if true, the osculum may be considered a sensory organ that is used to coordinate whole animal responses in sponges. Arrays of primary cilia like these could represent the first step in the evolution of sensory and coordination systems in metazoans.
In a separate paper – ‘The analysis of eight transcriptomes from all Porifera classes reveals surprising genetic complexity in sponges’, her lab found –
Our analyses showed that all sponge classes share an unexpectedly large complement of genes with other metazoans. Interestingly, hexactinellid, calcareous and homoscleromorph sponges share more genes with bilaterians than with non-bilaterian metazoans. We were surprised to find representatives of most molecules involved in cell-cell communication, signaling, complex epithelia, immune recognition and germ-lineage/sex, with only a few, but potentially key, absences.
All those exciting results are summarized in her recent review – ‘Elements of a ‘nervous system’ in sponges’.
Casey Dunn and siphonophores
Casey Dunn’s lab focuses on siphonophores. If you do not know anything about those strange animals, please take a look at this beautiful site prepared by him. In his research, he combines biological methods and bioinformatics to study these strange creatures, and we mentioned some of his papers in the evolutionary biology section. Curious readers may start from his 2008 Nature paper and continue to two recent ones uploaded in biorxiv.
The Histology of Nanomia bijuga (Hydrozoa: Siphonophora)
The siphonophore Nanomia bijuga is a pelagic hydrozoan (Cnidaria) with complex morphological organization. Each siphonophore is made up of many asexually produced, genetically identical zooids that are functionally specialized and morphologically distinct. These zooids predominantly arise by budding in two growth zones, and are arranged in precise patterns. This study describes the cellular anatomy of several zooid types as well as of the stem and gas-filled float, called the pneumatophore. The distribution of cellular morphologies across zooid types enhances our understanding of zooid function. The unique absorptive cells in the palpon, for example, indicate specialized intracellular digestive processing in this zooid type. Though cnidarians are usually thought of as mono-epithelial, we characterize at least two cellular populations in this species which are not connected to a basement membrane. This work provides a greater understanding of epithelial diversity within the cnidarians, and will be a foundation for future studies on Nanomia bijuga, including functional assays and gene expression analyses.
Stem cells in a colonial animal with localized growth zones
Siphonophores (Hydrozoa) have unparalleled colony-level complexity, precision of organization, and functional specialization between zooids (i.e., the units that make up colonies). Previous work has shown that, unlike other colonial animals, most growth in siphonophores is restricted to one or two well-defined growth zones that are the sites of both elongation and zooid budding. To understand this unique growth at the cellular level, we characterize the distribution of interstitial stem cells (i-cells) in the siphonophore Nanomia bijuga. Within the colony we find that i-cells are present at the tips of the growth zones, at well-defined sites where new zooid buds will arise, and in the youngest zooid buds. As each zooid matures, i-cells become progressively restricted to specific regions until they are mostly absent from the oldest zooids. We find no evidence of the migratory i-cells that have been observed in colonial cnidarian relatives. The restriction of i-cells to particular developing structures and sites of growth suggest a plant-like model of growth for siphonophores, where the growth zones function much like meristems. This spatial restriction of stem cells could also explain the precision of colony-level organization in siphonophores as a consequence of restricted growth potential.
Is animal evolution gain in complexity or rearrangement of existing complexity?
All these exciting work may completely overhaul our understanding of evolution. If sponges and jellies have the same genetic toolkit as humans and functions like ‘nervous system’, is animal evolution rearrangement of existing complexity prepackaged in unicellular protists, such as choanoflagelletes? Does that mean the complexity came primarily from the unexplained evolution of eukaryote from prokaryote? That is puzzling, because the prokaryote–>eukaryote evolution is seen as saltatory based on evidences collected so far. Hopefully, recent technological advances will help us recover various missing blocks in fundamental understanding of evolution from prokaryote–>eukaryote.
I found the book “Genomic Control Process – Development and Evolution” by Professors Isabelle Peter and Eric Davidson very informative and thought-provoking, and contacted its authors to check whether they would be interested in publishing an interview to be shared with our readers. I am greatly honored that they agreed about not one, but two interviews. The first one (see below) is email-based, where they replied to a set of questions regarding their book sent by me. A video interview will follow next month.
Professor Davidson had been the source of inspiration for my work for many years. I first met him about a decade back, when I drove to Caltech to discuss about the possibility of using tiling arrays for the sea urchin genome project. I prepared a number of slides to make a convincing case, and was pleasantly surprised to find that he already knew far more about the technology than what I had in my slides. Then three years later (2007), Davidson was the first to warn me that the arrays would go away and be replaced by Illumina short-read sequencing.
The truly visionary aspect of his group’s research is in taking advantage of such technological advances to answer how the genomic features are linked to biological phenomena. In a series of recent papers, Dr. Peter and Dr. Davidson reported about making major empirical and conceptual breakthroughs and their book resulted from that collaborative work. However, the book is not limited to their own work, but provides novel synthesis for a large spectrum of ‘evo-devo’ in animals.
The questions and answers are enclosed below.
1. Would you please give us a brief summary of what the book is about?
Peter/Davidson: This book is about the mechanisms by which the linear genomic DNA sequence encodes major processes of animal life, the most demanding of which is development. In this book we have treated a vast array of biological phenomena, by organizing them around a framework concept, the concept of gene regulatory networks. These networks are systems of interacting regulatory genes, which ultimately determine the spatial and temporal expression of all genes in the developing animal. The same arguments inform what has long been regarded as the most fundamental problem in biology, which is how evolution works. In our book we have dealt with mechanisms of gene regulation in animal cells, the mechanisms of development in many different contexts, and the mechanisms by which animal body plans have diverged in deep time. What this book is really about is how the fundamental principles of genomic information use give us an explanatory framework and enables us to see any aspects of animal life through that same lens.
2. What aspects of animal life is this book focused on?
Peter/Davidson: There are four large general areas for which this book provides an in-depth interpretation. The first of these areas deals with the molecular biology of gene regulatory networks and evaluates how sequence-specific gene regulation is achieved in animal cells. Several regulatory mechanisms, such as transcriptional regulation, non-coding RNAs and epigenetic histone modifications, are discussed, all of which ultimately depend on the sequence recognition function of transcription factors. Second, we consider the function of gene regulatory networks in controlling the processes of development from egg to embryo, from embryo to body part, and from body part to cell types. Third we consider the functional import of the structure of developmental networks. Three very important aspects that we discuss in depth are the deep hierarchy of these networks; their modular structure, in that they are composed of what seems to be a finite set of subcircuit architectures; and their primary function in organizing an increasingly complex landscape of spatial expression domains. We also compare diverse computational approaches to network function. Fourth, we consider evolutionary process as the outcome of change and stasis since the beginning of the Cambrian, in the structure of developmental networks encoded in animal genomes.
3. Are there areas outside development and evolution per se that your book impacts?
Peter/Davidson: The book has broad implications for many contiguous areas of bioscience, in addition to development and evolution. These include the mechanisms of mobilization of effector genes, often of medical significance, that do all the work of differentiated cells, and many kinds of physiological response. All of these ultimately require understanding of genomic control mechanisms, a subject that converges on the basic theoretical conceptions of this book. This casts in a new light the definition of functional genomics, in that the functional genome consists of the components of gene regulatory networks, largely those encoding developmental process.
4. What audience is the book addressed to?
Peter/Davidson: We have written the book with a broad audience in mind, essentially anyone who has a background in science or engineering and some basic level of familiarity with molecular biology. Although the arguments of the book arrive at the growing point of knowledge, concepts and processes are all defined from the ground up, so that anyone who cares can follow. We have deliberately sought to write this book on two simultaneous parallel planes: readers concerned with the major ideas and concepts can enjoy these without emerging into biological detail, while those concerned with experimental evidence will find ample representation of this level of reality, particularly in the figures.
5. Is this book comparable to a textbook or an extended review of a large field of developmental biology?
Peter/Davidson: This book is not a review of received wisdom, but a novel synthesis informed by diverse areas of biology. We feel that a synthesis is particularly important in our time, when there is a general sense that biology has become an overwhelming mass of context-specific details and data that make the extraction of broad and incisive mechanistic principles utterly impossible. Although in a conventional sense this book is not a textbook, we have used it as a basis for a new mode of concept-oriented teaching.
6. What is the rationale for the novel synthesis you mention?
Peter/Davidson: Many aspects of biology depend directly on information carried in the genome, and the control system for genomic function thus represents something like a common denominator of biology. Indeed, genomic control logic provides a common mechanistic basis for the most disparate processes, ranging from specific cell function to embryogenesis to making of the body plan to body plan evolution. Being able to think about these processes in common mechanistic terms offers an immensely powerful tool to compare and relate traditionally distinct aspects of animal biology.
7. In Chapter 6 you present your new computational Boolean treatment of developmental gene regulatory networks: what is its significance?
Peter/Davidson: This model was a successful attempt to utilize the experimentally defined regulatory interactions of a developmental gene regulatory network to reconstruct in silico developmental gene expression in time and space, with very considerable accuracy. The result was a proof of principle that causality in gene expression, i.e. the basis of development, lies in encoded gene regulatory networks, and that such networks can be experimentally solved. This work also shows that experimentally studying gene regulatory networks represents the most important pathway towards understanding large areas of biological process. Thus the Boolean model unlocks a major conceptual road to the future.
Homolog.us blog thanks the publisher (Elsevier) for sharing a chapter with our readers and for sponsoring our work. If you are purchasing at the Elsevier online bookstore, please use the code BIOMED315 to get a 30% discount on the price.
Sometimes you come across examples convincingly showing that the publishing world has gone insane. I came across the suggestion of an interesting book – “How to Succeed in School Without Really Learning: The Credentials Race in American Education”, and decided to check at Amazon. It costs $25, but you can buy almost new used copies for $10.
Before hitting the ‘buy’ button, I decided to check for online reviews and came across a review by John F. Covaleskie in a journal. Strangely, the review costs $40, on top of which you will have to pay bunch of other taxes like VAT !!
How to Succeed in School without Really Trying: The Credentials Race in American Education, by David F. Labaree
Anyone with understanding of free market would expect that a review from 1999 to cost a lot less than the used book. So, the above demonstration suggests that ‘free market’ does not exist in the publishing market. Is it monopoly pricing (cartel pricing) or something more?
A few weeks back, Nobel Laureate Tim Hunt was fired from his job. It was caused by a journalist declaring Hunt as a ‘diversity witch’ in twitter, leading to moral panic of the masses and subsequent dismissal of Hunt. A new article argues that “The Royal Society’s ‘Diversity Committee’ Pre-Judged #TimHunt. Now UCL Should Give Him Due Process“.
In his professional life Sir Tim Hunt has an active record of mentoring and promoting women that have been his students. He has never asked for single-sex labs or advocated for them. Eminent female scientists that have studied under him, including Professor Hyunsook Lee, Professor of Biological Sciences at Seoul Unversity, have come forward to say so.
On Jun 7th, journalist Connie St Louis tweeted a partial account of Sir Tim’s words leaving out “Now seriously….” and his praise of women in science. She insisted that he was deadly serious and had not praised the role of women in science. She also stated Sir Tim had ‘thanked the women present for making the lunch because that was their role’
Some journalists present, like Deborah Blum, backed her account in tweets. Others denied it.
Hunt’s full quote was given in the article:
Let me tell you about my trouble with girls. Three things happen when they are in the lab: you fall in love with them, they fall in love with you, and when you criticise them they cry. Perhaps we should make separate labs for boys and girls? Now, seriously, I’m impressed by the economic development of Korea. And women scientists played, without doubt an important role in it. Science needs women, and you should do science, despite all the obstacles, and despite monsters like me.
If Hunt is restored, that should lead to some soul-searching of twitter crowd. The best book to follow in this context is Douglas Rushkoff’s ‘PRESENT SHOCK: When Everything Happens Now’. Also, the movie ‘We Live in Public’ is worth seeing.
Speaking of ‘Present Shock’ –
In his new book, PRESENT SHOCK: When Everything Happens Now (Current; March 15, 2013), Rushkoff introduces the phenomenon of presentism, or – since most of us are finding it hard to adapt – present shock. Alvin Toffler’s radical 1970 book, Future Shock, theorized that things were changing so fast we would soon lose the ability to cope. Rushkoff argues that the future is now and we’re contending with a fundamentally new challenge. Whereas Toffler said we were disoriented by a future that was careening toward us, Rushkoff argues that we no longer have a sense of a future, of goals, of direction at all. We have a completely new relationship to time; we live in an always-on “now,” where the priorities of this moment seem to be everything.
Rushkoff identifies the five main ways we’re struggling, as well as how the best of us are thriving in the now:
1. Narrative collapse – the loss of linear stories and their replacement with both crass reality programming and highly intelligent post-narrative shows like The Simpsons. With no goals to justify journeys, we get the impatient impulsiveness of the Tea Party, as well as the unbearably patient presentism of the Occupy movement. The new path to sense-making is more like an open game than a story.
2. Digiphrenia – how technology lets us be in more than one place – and self – at the same time. Drone pilots suffer more burnout than real-world pilots, as they attempt to live in two worlds – home and battlefield – simultaneously. We all become overwhelmed until we learn to distinguish between data flows (like Twitter) that can only be dipped into, and data storage (like books and emails) that can be fully consumed.
3. Overwinding – trying to squish huge timescales into much smaller ones, like attempting to experience the catharsis of a well-crafted, five-act play in the random flash of a reality show; packing a year’s worth of retail sales expectations into a single Black Friday event – which only results in a fatal stampede; or – like the Real Housewives – freezing one’s age with Botox only to lose the ability to make facial expressions in the moment. Instead, we can “springload” time into things, like the “pop-up” hospital Israel sent to Tsunami-wrecked Japan.
4. Fractalnoia – making sense of our world entirely in the present tense, by drawing connections between things – sometimes inappropriately. The conspiracy theories of the web, the use of Big Data to predict the direction of entire populations, and the frantic effort of government to function with no “grand narrative.” But also the emerging skill of “pattern recognition” and the efforts of people to map the world as a set of relationships called TheBrain – a grandchild of McLuhan’s “global village”.
5. Apocalypto – the intolerance for presentism leads us to fantasize a grand finale. “Preppers” stock their underground shelters while the mainstream ponders a zombie apocalypse, all yearning for a simpler life devoid of pings, by any means necessary. Leading scientists – even outspoken atheists – prove they are not immune to the same apocalyptic religiosity in their depictions of “the singularity” and “emergence”, through which human evolution will surrender to that of pure information.
In case of Tim Hunt, the twitter crowd made a quick judgement based on inauthentic ‘authority’ and pre-existing bias, because they had to deal with a large number of world crisis in a short time, thanks to ‘present shock’. That, in turn, started the ‘We live in public’ feedback loop at UCL leading to Hunt’s quick dismissal, because every problem has to be solved within internet time.
Kallisto is an efficient program for RNAseq quantification published by Lior Pachter’s lab. We wrote about it in “Lightweight Algorithms for RNAseq Expression Analysis – Sailfish, Kallisto and Salmon” and also pointed out its unconventional license. The issue of non-MIT/GPL license seems to have created a twitter storm, but speaking of ‘Kallisto’, we need to remember that the word refers to three aspects coming in one package –
i)Kallisto as an intellectual contribution in algorithm development
RSEM, the previously used algorithm for RNAseq quantification, was alignment-based and took days to weeks to perform simple analysis. Most likely the expectation minimization step took too long to converge. As an alternative, Patro and Kingsford developed Sailfish and it was huge improvement in terms of time performance at some cost of accuracy. Kallisto recovers the lost accuracy of RSEM, but keeps the time performance of Sailfish. That is an important contribution in algorithm worthy of getting credit.
ii)Kallisto as high quality code with open access
Páll Melsted, who led the code development, is an expert in writing bioinformatics code, and you can see the quality in Kallisto. Of course, you can see it only because the code is available as open source.
iii)Kallisto as a business model
As we mentioned, Kallisto comes with non-GPL, non-MIT license.
Will you use it?
On point (i) (“Kallisto as an intellectual contribution in algorithm development”), we will definitely use Kallisto, because good algorithms are hard to say no to.
On point (ii) (“Kallisto as high quality code with open access”), we will most likely use Kallisto, until someone else develops high quality alternative. Maybe Patro’s Salmon is already there.
On point (iii) (“Kallisto as a business model”), we will never use Kallisto codes to build or distribute a larger library, because it corrupts the licenses of all other programs. A good example of that corrupting effect is Kallisto code itself. You can see that it reused some libraries distributed by Heng Li under MIT license, but the entire package has a stricter license.
What’s the alternative for (iii)?
Well, two things can happen.
Maybe the algorithm is so complex, Páll Melsted’s code is so good and Bray/Pimentel/Melsted/Pachter spend so much time in incorporating new algorithmic modifications and versions that it is impossible to create an alternative. Then everyone should suck up and bow to Kallisto’s authors. After all, the largest user base of the program lives in the universities and will not have to pay for it anyway.
The other extreme is that the program becomes a huge commercial success even though it is easy to reproduce by carefully studying and the authors do not make any update. In that case, someone will think that its license is a lousy deal, write a different (ii) (“high quality code with open access”) based on Kallisto algorithm and distribute under MIT/BSD.
Let us wait to determine which approximate path the users take.
This new paper comes from G. Marçais, Alex Zimin and Jim Yorke of minimizer fame.
Illumina Sequencing data can provide high coverage of a genome by relatively short (most often 100 bp to 150 bp) reads at a low cost. Even with low (advertised 1%) error rate, 100 × coverage Illumina data on average has an error in some read at every base in the genome. These errors make handling the data more complicated because they result in a large number of low-count erroneous k-mers in the reads. However, there is enough information in the reads to correct most of the sequencing errors, thus making subsequent use of the data (e.g. for mapping or assembly) easier. Here we use the term “error correction” to denote the reduction in errors due to both changes in individual bases and trimming of unusable sequence. We developed an error correction software called QuorUM. QuorUM is mainly aimed at error correcting Illumina reads for subsequent assembly. It is designed around the novel idea of minimizing the number of distinct erroneous k-mers in the output reads and preserving the most true k-mers, and we introduce a composite statistic π that measures how successful we are at achieving this dual goal. We evaluate the performance of QuorUM by correcting actual Illumina reads from genomes for which a reference assembly is available.
We produce trimmed and error-corrected reads that result in assemblies with longer contigs and fewer errors. We compared QuorUM against several published error correctors and found that it is the best performer in most metrics we use. QuorUM is efficiently implemented making use of current multi-core computing architectures and it is suitable for large data sets (1 billion bases checked and corrected per day per core). We also demonstrate that a third-party assembler (SOAPdenovo) benefits significantly from using QuorUM error-corrected reads. QuorUM error corrected reads result in a factor of 1.1 to 4 improvement in N50 contig size compared to using the original reads with SOAPdenovo for the data sets investigated.
QuorUM is distributed as an independent software package and as a module of the MaSuRCA assembly software. Both are available under the GPL open source license at http://www.genome.umd.edu.
Readers may also take a look at Heng Li’s error correction program
published preprinted early this year. |