Category Archives: Research

computational microRNA target prediction architecture for human transcriptome

A new article in Bioinformatics tries to tackle the question of which microRNA’s go with their target messenger RNA’s, which is no small computational task.
Here’s the abstract:

MicroRNAs (miRNAs) play an essential task in gene regulatory networks by inhibiting the expression of target mRNAs. As their mRNA targets are genes involved in important cell functions, there is a growing interest in identifying the relationship between miRNAs and their target mRNAs. So, there is now an imperative need to develop a computational method by which we can identify the target mRNAs of existing miRNAs. Here, we proposed an efficient machine learning model to unravel the relationship between miRNAs and their target mRNAs.

We present a novel computational architecture MTar for miRNA target prediction which reports 94.5% sensitivity and 90.5% specificity. We identified 16 positional, thermodynamic and structural parameters from the wet lab proven miRNA:mRNA pairs and MTar makes use of these parameters for miRNA target identification. It incorporates an Artificial Neural Network (ANN) verifier which is trained by wet lab proven microRNA targets. A number of hitherto unknown targets of many miRNA families were located using MTar. The method identifies all three potential miRNA targets (5′ seed-only, 5′ dominant, and 3′ canonical) whereas the existing solutions focus on 5′ complementarities alone.

MTar, an ANN based architecture for identifying functional regulatory miRNA-mRNA interaction using predicted miRNA targets. The area of target prediction has received a new momentum with the function of a thermodynamic model incorporating target accessibility. This model incorporates sixteen structural, thermodynamic and positional features of residues in miRNA: mRNA pairs were employed to select target candidates. So our novel machine learning architecture, MTar is found to be more comprehensive than the existing methods in predicting miRNA targets, especially human transcritome.

HIV and the T Cell Life Cycle

In an excellent review of a paper in the Journal of Biology (“Generalized immune activation as a direct result of activated CD4+ T cell killing“), Nienke Vrisekoop , Judith N Mandl, and Ronald N Germain discuss the life and death of the T lymphocyte.

T lymphocytes have a difficult existence. As mature cells, they are essential for immunity to infection, but in the early stages of their development in the thymus, more than 90% of them fail selection for the appropriate antigen receptors and die before export to the peripheral immune system. Those that achieve maturity spend weeks, months or even years circulating through the body, in constant search of a foreign antigen that their antigen-specific receptor can recognize, and needing continuously to compete for trophic signals necessary for their survival. Most fail to find an antigenic match and remain as small resting cells until death. A few encounter the right partner and undergo a transient bout of exponential clonal expansion, only for more than 90% of these progeny to be lost by apoptosis shortly after the antigen is cleared. The remaining 10% are maintained as memory cells (Figure 1), conferring lasting protection.

Understanding the mechanism of T cell death is a major concern when confronting HIV and its progression into full blown AIDS.

Although it is known that HIV kills activated CD4+ T cells, it is still a major unresolved question why these cells progressively decline after infection. It is clear that in infected individuals, the rate of loss of CD4+ T cells is greater than the rate of production so that the CD4+ T cell pool is gradually eroded over time, but it remains to be determined how the balance between these processes is impaired. It is unlikely that direct killing of infected target cells by HIV is sufficient to cause CD4+ T cell depletion. Natural hosts for simian immunodeficiency virus (SIV), such as sooty mangabeys, do not progress to AIDS and maintain near-normal levels of peripheral CD4+ T cell numbers despite high rates of viral replication [4]. In fact, the level of immune activation is a better predictor of disease progression than viral load. Consistent with this, HIV infection in humans leads to chronic generalized immune activation characterized by an increased rate of exit of CD4+ and CD8+ T cells and of natural killer (NK) cells from the resting state, increased T and NK cell turnover and death, polyclonal B cell activation with increased levels of gamma globulins, and elevated production of pro-inflammatory cytokines. Conversely, chronic immune activation is not seen following SIV infection in natural hosts that do not show progression to AIDS [4].

That is, there is a question as to what causes the autoimmune response that is so devastating to people with AIDS.  There are two proposed methods of activation.  The first is that chronic activation of the hosts immune system disrupts CD4+T cell homeostasis.  The second is the opposite, that HIV drops the CD4+T count out of homeostasis and the bodies over-active response is chronic immune activation.  The authors make the point that these two possibilities are not incompatible.

Clearly, the two possible causal relationships between chronic immune activation and CD4+ T cell loss are not mutually exclusive. In fact, chronic immune activation and the loss of CD4+ T cells may amplify each other in a loop that makes it difficult to establish which process underlies and drives the other.

The study in review attempted to induce this same response in mice.

Marques et al. [1] suggest that the OX40-DTA mouse is one approach to this issue and that the findings in these mice provide important insight into the control of lymphocyte dynamics in infected humans. Indeed, in the absence of exogenous infection, OX40-DTA mice do show features consistent with generalized immune activation (Table 1), including an expansion of effector CD8+ T cell numbers that inverts the usual CD4+:CD8+ T cell ratio, and increased serum levels of inflammatory cytokines. This generalized activation cannot be attributed to the release of microbial components into the circulation from the gut, because deletion of activated CD4+ T cells does not in itself lead to a breach in the gut epithelium. Notably, Marques et al. [1] show that the expansion of effector CD8+ T cells and increases in serum levels of inflammatory cytokines can be reversed following reintroduction of Tregs from normal mice, suggesting that the increased immune activation in OX40-DTA mice can in part be ascribed to a Treg insufficiency, which they propose is a key event in HIV-infected individuals leading to CD4+ T cell depletion.

There’s a lot more, and the review goes into much more detail.  But, I can see how this approach could be fruitful in illuminating the underlying causes of a disease that plagues such a large number of humans on the planet.

Parochial Altruism and War: A Game Theoretic Analysis

Pleistocene North America

North America during the Pleistocene

War, what is it good for?  Apparently, altruism.  In a paper published in Science, Samuel Bowels and Jung-Kyoo Choi took a game-theoretic approach to studying the evolutionary roots of both altruism and parochialism.  They concluded that neither would have likely evolved alone, but instead co-evolved, together being a powerful combination in the survival kit  of our Pleistocene and early Holocene ancestors.


Altruism–benefiting fellow group members at a cost to oneself–and parochialism–bostility toward individuals not of one’s own ethnic, racial, or ther group–are common human behaviors.  The intersection of the two–which we term “parochial altruism”–is puzzling from an evolutionary perspective because altruistic or parochial behavior reduces one’s payoffs by comparison to what one would gain by eschewing these behaviors.  But parochial altruism could have evolved if parochialism promoted intergroup hostilities and the combination of altruism and parochialism contributed to success in these conflicts.  Our game-theoretic analysis and agent -based simulations show that under conditions likely to have been experienced by late Pleistocene and early Holocene humans, neither parochialism nor altruism would have been viable singly, but by promoting group conflict, they could have evolved jointly.


Even Darwin noted that war was a powerful tool “used” by evolution to increase  altruism and solidarity toward ones own group members.  But, there have been two major questions lingering.

  1. What is the process by which war became common enough to support the evolution of altruism in this context?
  2. What is the likelyhood that altruism itself (conditioned on group membership) contributed to the high levels of lethal intergroup conflict among humans?

Neither of these questions has been well enough analyzed and was one of reasons the authors did their study.    Empirically, both altruism and hostility are quite important to members of other groups.

The empirical importance of both altruism and hostility to members of other groups is well established.  Experimental and other evidence demonstrates that individuals often willingly give to strangers, reward good deeds, and punish individuals who violate social norms, even at a substantial personal cost (4), while favoring fellow group members over “outsiders” in the choice of friends, exchange partners, and other associates and in the allocation of valued resources (5).

They site an example of a case in Papua New Guinea, “There exists strong favoritism toward ones-own linguistic group in giving to others,”  and a higher tendency to punish those from different linguistic groups.

They use the term Parochial Altruism in reference to a person to mean that when a person engages in hostile and aggressive behavior with another group, this person incurs a mortal risk, therefore a fitness loss verses those who refrain from such aggression.

Knowing Parochial altruism exists and assuming that neither Parochialism nor Altruism would have evolved in an environment (that is survived a selection process) that favored some other trait that resulted in higher payoffs, then how DID Parochial Altruism evolve?

A Solution

One possibility is that since oiur ancestors lived in a hostile environment where resources were scarce, Parochial Altruism could have evolved and thrived because those groups with high numbers of Parochial Altruists would have been more able to engage in aggressive action and “win” on behalf of their groups.

The two most important correlates of tribal warfare are natural disasters and resource scarcity.  The Pleistocene and early Holocene (roughly 125,000 to 10,000 years ago) are known to have been times of substantial volatility.  They also coincide with the most significant periods of human evolution.

Could Parochial Altruism have evolved in such a climate?

The Game

Bowel’s and Choi’s model consists of 4 types of players.

  1. PA:  Parochial Altruists
  2. TA: Tolerant Altruists
  3. PN: Parochial Non-Altruists
  4. TN: Tolerant Non-Altruists

Note that Parochials of both types are hostile toward other groups.  But, ONLY Parochial Altruists will engage in combat.  This is because PN’s won’t risk death for the benefit of others.

Their model has two types of selection acting at once.  Intra-Group selection favors TN’s and tends to eliminate PA’s.  And, Inter-Group selection which favors PA’s via selective extinction.

In a purely risk vs. reward scenario, it makes little sense to be a PA.  While there exists two benefits to winning a war (namely 1. Greater chance of future survival, 2. Opportunity to reproduce, thereby replacing those PA’s lost in war), the risk of mortal death incured by war “offsets this direct benefit by a wide margin.”  Therefore, each PA would be better off adopting a different strategy, in terms of their own reproductive fitness.  This confirms that PA’s are, indeed, altruistic according to the traditional meaning of the term.

3 Stage Game

The game runs in 3 stages.   In stage one, when two groups A and B meet, there is a probability that they will engage hostilely.  If they do not, then the game ends.  If  their interaction is hostile, they move on to stage two.

Stage two, given that their interaction is hostile, there is a new probability that A and B will goto war.  If they don’t, they move on, game is done.  If they do, stage 3.

Stage 3, they are now at war, the group with the higher number of PA’s has a higher probability of winning.  If this group is A, then A is more likely to win a war against the PA deficient group B.   Given that A is stronger (ie, has more PA’s) there are two options:  A and B draw, and the result is simply that both groups lose a certain number of fighters (PA’s); or A wins, and still loses a certain number of fighters, but also now gains a number of replicas that make up for that loss.

From B’s perspective, given that B is weaker (has less PA’s), there is only Draw or Lose. B could get lucky and draw, and only lose some PA’s.  But, there is a higher likelyhood of a loss.  In this case, B loses both fighters (PA’s) and civilians (made up of the other types).

In the paper they are quite explicit about what these probabilities are and why they chose them.  But, the point is that not every encounter with another group is hostile, not every hostile interaction results in war, and every war is won with a higher probability if you have a large number of PA’s.


They ran this game through a number of iterations accounting for hundreds of generations.  They found that transitions from quite tolerant non-altruistic (read: peaceful) groups to bellicose parochial altruistic groups can happen very rapidly–in about 200 generations, or about 5,000 years.

The markedly higher reproductive success of predominantly parochial altruist groups when interacting with groups with fewer parochial altruists could therefore explain the rapid range expansions that are thought to be common among some late Pleistocene human groups, and thus may partly explain sthe still puzzling second great hominid diaspora that swept from Africa as far as Australia in the course of no more than 10 millennia.

This study aids in the study of why group boundaries have such a profound effect on human behavior, from an evolutionary perspective.

In conclusion they add:

We have explained how Homo Sapiens could have become a warlike yet altruistic species.  But there is no evidence that the hypothetical alleles in our model exist, or that were they to exist they could be expressed in the complex behaviors involved in helping others and engaging in lethal conflict.  Theus, we have not shown that a warlike genetic predisposition exists, only that should one exist, it might have coevolved with altruism and warfare in the way that we have described.

They make a good closing point.  Theoretical (ie, mathematical) biology doesn’t “prove” that certain things are true.  It tests the validity of certain hypothesis and ideas, thereby opening up further possibilities for empirical research.


Choi, Jung-Kyoo, and Samuel Bowles. 2007. The Coevolution of Parochial Altruism and War. Science 318, no. 5850 (October 26): 636-640. doi:10.1126/science.1144237.

PMC-BioPhysics: A New Open Access Journal

“I am very pleased to be working with PhysMath Central as I believe open access is the future for publication of all bio-related research. I am also excited at the prospect that online publishing brings the ability to post video and raw data as supplementary to each article, and hope our authors will make extensive use of this ability.”

Huan-Xiang Zhou, Editor-in-Chief – PMC Biophysics

As a graduate student I have free access through my Universities library to any journal I want (well, most of them anyway).  But, not everyone has this luxury including most readers of this blog.  If I write an article here with a reference at the bottom to an article in a Springer Journal (I’m not pointing fingers … actually, I AM pointing fingers), then nearly no one is going to be able to go and read the original source article themselves–it’s way too expensive.  With these articles, anyone anywhere can access them for free.

I believe the free and open access to high-level research is immensely important in a democracy.

PhysMath Central (from the creators of BioMed Central) have recently launched a new Open Access journal, PMC BioPhysics.  This journal, like all journals at PhysMath and BioMed, is Zotero ready.  Very handy for those of us suffering from the perpetual problem of organizing our research collections.

By the look of the first issue, PCM Biophysics will likely be a very cool read, indeed.  Below”is the abstract to the article, “The multiple faces of self-assembled lipidic systems“.

Lipids, the building blocks of cells, common to every living organisms, have the propensity to self-assemble into well-defined structures over short and long-range spatial scales. The driving forces have their roots mainly in the hydrophobic effect and electrostatic interactions. Membranes in lamellar phase are ubiquitous in cellular compartments and can phase-separate upon mixing lipids in different liquid-crystalline states. Hexagonal phases and especially cubic phases can be synthesized and observed in vivo as well. Membrane often closes up into a vesicle whose shape is determined by the interplay of curvature, area difference elasticity and line tension energies, and can adopt the form of a sphere, a tube, a prolate, a starfish and many more. Complexes made of lipids and polyelectrolytes or inorganic materials exhibit a rich diversity of structural morphologies due to additional interactions which become increasingly hard to track without the aid of suitable computer models. From the plasma membrane of archaebacteria to gene delivery, self-assembled lipidic systems have left their mark in cell biology and nanobiotechnology; however, the underlying physics is yet to be fully unraveled.

Sound cool?  Hey, you can check out the whole article here for free.  Ah … freedom.

Want Soup? Try Prebiotic

I love this stuff:

The blue arrows represent the obvious route to RNA, going from prebiotic compounds (marked here by 7,8, and 10) to nucleobases (3) and ribose (4). And the big red X shows the point at which this route fails.

Sutherland and his colleagues started with the same ingredients, but cooked them in a different recipe, marked in green. Instead of trying to build the two parts independently, the scientists instead built a single molecule that had more and more components of the two parts already in place. They used just four reactions, all of which worked efficiently, to get one of the four ribonucleotides, known as cytidine. At the end of the process, the scientists zapped the mix with ultraviolet light (something that would be easy to come by on the early Earth, unprotected by an ozone layer). They eliminated some of the unwanted side products and turned some of the cytidine into another unit of RNA, known as uracil.

The Recipe of Life.  You think the food network would be interested in a show?

Tuberculosis Diversity and Genetic Drift

Bacteria often provide vivid examples of how powerful the forces of evolution can be.  In keeping with that, Hershberg, et al., in a paper published in PLoS, show that evolutionary forces may increase the number of drug-resistent strains of Mycobacterium Tuberculosis (MTB).

They attribute the increase of these strains to both human demographic conditions (global travel, urbanization, population growth) and genetic drift.

This is a case when the intersection of evolution and of economics can have an unsavory effect.  Every 15 seconds a person dies of MTB.

Furthermore, we found that the global diversity in tuberculosis strains can be linked to the ancient human migrations out of Africa, as well as to more recent movements that followed the increases of human populations in Europe, India, and China during the past few hundred years. Taken together, our findings suggest that the evolutionary characteristics of tuberculosis bacteria could synergize with the effects of increasing globalization and human travel to enhance the global spread of drug-resistant tuberculosis.


High Functional Diversity in Mycobacterium tuberculosis Driven by Genetic Drift and Human Demography Hershberg R, Lipatov M, Small PM, Sheffer H, Niemann S, et al. PLoS Biology Vol. 6, No. 12, e311 doi:10.1371/journal.pbio.0060311

A Review: The Hitchhiker’s Guide to Altruism: Gene-culture Coevolution and the Internalization of Norms

In an article for the Journal of Theoretical Biology, Herbert Gintis provides a model that shows that:

“if an internal norm is fitness enhancing, then for plausible patterns of socialization, the allele for the internalization of norms is evolutionarily stable.”

Further he posits that this view can be used to model Herbert Simon’s 1990 explanation of altruism.  Simon’s idea is that altruistic norms “Hitchhike” on the backs of the general tendencies of internal norms to be “personally fitness enhancing”.

OK, cool, so what is an “internal norm”?  It’s a pattern of behavior that is regulated by internal controls or “sanctions”.  We’d think of these like shame or guilt, the little guy sitting on your shoulder with the white outfit arguing against the little guy on the other shoulder in the red outfit.

Gintis makes the point that our very capacity to internalize norms like guilt and shame means that humans have what he calls “socially programmable” objective functions.  An objective function is an economics idea.  The point is that humans have these functions (that we can objectively model) that they try to optimize (or maximize) subject to particular constraints.

So, human behavior is dependent not only on the beliefs they hold about their objective functions (if I choose to take action A, then the outcome is result R), but also on their “values”.  The values are the goals, or the point of why they would take a particular action in the first place.

He goes on:

“Suppose there is one genetic locus that controls the capacity to internalize norms.  I develop models of gene-cultural coevolution to show that if an internal norm is fitness enhancing, then the allele for internalization of norms is evolutionarily stable.  Moreover, if the fitness payoff to the internalized norm is sufficiently large, or if there is a sufficiently high rate of phenotypic level assortative mating, the allele for internalization is globally stable.”

It’s important to discuss what he means by “evolutionarily stable”.  The idea was developed by John Maynard Smith.  In his book, “Evolution and the Theory of Games.”, he describes it as such:

“A ‘strategy’ is a behavioral phenotype; ie, it is a specification of what an individual will do in any situation in which it may find itself.  An ESS (Evolutionarily Stable Strategy) is a strategy such that, if all the members of a population adopt it, then no mutant strategy could invade the population under the influence of natural selection.”

Gintis has been spearheading a move for the past 20 or 30 years to make evolutionary game theory (and the use of the ESS) the standard in Social Science research modeling, as opposed to classical game theory.  But, that’s another topic.

He is attempting to make a case, in this article, that people value behavior that can be described as altruistic (bravery, fairness, empathy, etc) for its own sake.  This is in contrast to the notion that people are altruistic because in the long term it is in their best interest.  This means that:

“A person who has internalized the value of ‘speaking truthfully’ will do so even in cases where the net payoff to speaking truthfully would otherwise be negative.”

Further, he argues that a norm will be more prevalent in a population if it is internalized by a the individuals in that population than if it is only followed when those individuals think it is in their best interest.

He uses his model to elucidate the way in which altruistic internal norms can drive out norms that are harmful both socially and to the individual.  He finds that altruistic cooperation and punishment (in his model) don’t depend on “repeated interaction, reputation effects, or multi-level selection”.  Even though an individual who caries the gene for altruistic behavior and the altruistic norm can suffer a personal cost (as per the definition of altruism), it doesn’t negatively affect the group.  That is, there is no in-group net negative effect.  It is in fact because of this pro-social effect that the strategy of the altruistic norm can be an ESS.

Basically, Gintis provides a model that shows that it is possible to fix an altruistic gene in a population for particular types of behavior that are good for the group as a whole, even through they hurt the individual.


  • Gintis, Herbert.  2003.  “The Hitchhiker’s Guide to Altruism: Gene-culture Coevolution, and the Internalization of Norms.”  Journal of Theoretical Biology. 220, 407-418.
  • Smith, John Maynard.  1982.  Evolution and the Theory of Games. Cambridge University Press.