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arXiv2015

The species problem and its logic: Inescapable Ambiguity and Framework-relativity

For more than fifty years, taxonomists have proposed numerous alternative definitions of species while they searched for a unique, comprehensive, and persuasive definition. This monograph shows that these efforts have been unnecessary, and indeed have provably been a pursuit of a will o' the wisp because they have failed to recognize the theoretical impossibility of what they seek to accomplish. A clear and rigorous understanding of the logic underlying species definition leads both to a recognition of the inescapable ambiguity that affects the definition of species, and to a framework-relative approach to species definition that is logically compelling, i.e., cannot not be accepted without inconsistency. An appendix reflects upon the conclusions reached, applying them in an intellectually whimsical taxonomic thought experiment that conjectures the possibility of an emerging new human species.

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arXiv2015

Markovian language model of the DNA and its information content

This work proposes a markovian memoryless model for the DNA that simplifies enormously the complexity of it. We encode nucleotide sequences into symbolic sequences, called words, from which we establish meaningful length of words and group of words that share symbolic similarities. Interpreting a node to represent a group of similar words and edges to represent their functional connectivity allows us to construct a network of the grammatical rules governing the appearance of group of words in the DNA. Our model allows to predict the transition between group of words in the DNA with unprecedented accuracy, and to easily calculate many informational quantities to better characterize the DNA. In addition, we reduce the DNA of known bacteria to a network of only tens of nodes, show how our model can be used to detect similar (or dissimilar) genes in different organisms, and which sequences of symbols are responsible for the most of the information content of the DNA. Therefore, the DNA can indeed be treated as a language, a markovian language, where a "word" is an element of a group, and its grammar represents the rules behind the probability of transitions between any two groups.

physics.bio-ph↗

arXiv2015

Towards life-long learning of posture control for s-EMG prostheses

Surface electromyography (s-EMG) sensors are a promising way to control upper-limb prostheses. However a training session is necessary in order to set up the controller that will make s-EMG based movement possible. All data recorded during the training session are used by a machine learning algorithm to make a posture classification, that will allow the controller to distinguish each posture. The aim of this study is to investigate if it's possible to make a posture classification which can remain valid over time. The next step will be the study of how it varies depending on the amount of information submitted to it during the training session in view of real life everyday use of the upper-limb prosthesis.

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arXiv2015

Understanding of Genetic Code Degeneracy and New Way of Classifying of Protein Family: A Mathematical Approach

The genetic code is the set of rules by which information encoded in genetic material (DNA or RNA sequences) is translated into proteins (amino acid sequences) by living cells. The code defines a mapping between tri-nucleotide sequences, called codons, and amino acids. Since there are 20 amino acids and 64 possible tri-nucleotide sequences, more than one among these 64 triplets can code for a single amino acid which incorporates the problem of degeneracy. This manuscript explains the underlying logic of degeneracy of genetic code based on a mathematical point of view using a parameter named Impression. Classification of protein family is also a long standing problem in the field of Bio-chemistry and Genomics. Proteins belonging to a particular class have some similar bio-chemical properties which are of utmost importance for new drug design. Using the same parameter Impression and using graph theoretic properties we have also devised a new way of classifying a protein family.

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arXiv2016

Stephane Leduc and the vital exception in the Life Sciences

Embryogenesis, the process by which an organism forms and develops, has long been and still is a major field of investigation in the natural sciences. By which means, which forces, are embryonic cells and tissues assembled, deformed, and eventually organized into an animal? Because embryogenesis deeply questions our understanding of the mechanisms of life, it has motivated many scientific theories and philosophies over the course of history. While genetics now seems to have emerged as a natural background to study embryogenesis, it was intuited long ago that it should also rely on mechanical forces and on the physical properties of cells and tissues. In the early 20th century, Stephane Leduc proposed that biology was merely a subset of fluid physics, and argued that biology should focus on how forces act on living matter. Rejecting vitalism and life-specific approaches, he designed naive experiments based on osmosis and diffusion to mimic shapes and phenomena found in living systems, in order to identify physical mechanisms that could support the development of the embryo. While Leduc's ideas then had some impact in the field, notably on later acclaimed D'Arcy Thompson, they fell into oblivion during the later 20th century. In this article I give an overview of Stephane Leduc's physical approach to life, and show that the paradigm that he introduced, although long forsaken, becomes more and more topical today, as developmental biology increasingly turns to physics and self-organization theories to study the mechanisms of embryogenesis. His story, I suggest, bears witness to our reluctance to abandon life-specific approaches in biology.

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arXiv2015

Massive Multi-Omics Microbiome Database (M3DB): A Scalable Data Warehouse and Analytics Platform for Microbiome Datasets

Massive Multi-Omics Microbiome Database (M3DB) is a data warehousing and analytics solution designed to handle diverse, complex, and unprecedented volumes of sequence and taxonomic classification data obtained in a typical microbiome project using NGS technologies. M3DB is a platform developed on Apache Hadoop, Apache Hive and PostgreSQL technologies. It enables users to store, analyze and manage high volumes of data, and also provides them the ability to query it in a fast and efficient manner. The M3DB framework includes command line tools to process and store microbiome data, along with an easy-to-use web-interface for uploading, querying, analyzing and visualizing the data and/or results. Availability: The source-code of M3DB is freely available for download at http://www.github.com/nisheth/M3DB.

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arXiv2015

Generalized Resemblance Theory of Evidence: a Proposal for Precision/Personalized Evidence-Based Medicine

Precision medicine emerges as the most important contemporary paradigm shift of medical practice but has several challenges in evidence formation and implementation for clinical practice. Precision/Personalized evidence-based medicine (pEBM) requires theoretical support for decision making and information management. This study aims to provide the required methodological framework. Generalized Resemblance Theory of Evidence mainly rests upon Generalized Theory of Uncertainty which manages information as generalized constraints rather than limited statistical data, and also Prototype Resemblance Theory of Disease which defines diseases/conditions when there is a similarity relationship with prototypes (best examples of the disease). The proposed theory explains that precisely-personalized structure of evidence is formed as a generalized constraint on particular research questions, where the constraining relation deals with averaged effect sizes of studies and its comparison to null hypothesis; which might be of either probabilistic or possibilistic nature. Similarity measures were employed to deal with comparisons of high-dimensional characteristics. Real examples of a meta-analysis and its clinical application are provided. This is one of the first attempts for introducing a framework in medicine, which provides optimal balance between generalizability of formed evidence and homogeneity of studied populations.

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arXiv2015

Simple cellular automata to mimic foraging ants submitted to abduction

Many species of ants forage by building up two files: an outbound one moving from the nest to the foraging area, and a nestbound one, returning from it to the nest. Those files are eventually submitted to different threats. If the danger is concentrated at one point of the file, one might expect that ants returning to the nest will pass danger information to their nestmates moving in the opposite direction towards the danger area. In this paper, we construct simple cellular automata models for foraging ants submitted to localized abduction, were danger information is transmitted using different protocols, including the possibility of no transmission. The parameters we have used in the simulations have been estimated from actual experiments under natural conditions. So, it would be easy to test our information-transmission hypothese in real experiments. Preliminary experimental results published elsewhere suggest that the behavior of foraging ants of the species Atta insularis is best described using the hypothesis of no transmission of danger information.

nlin.AO↗

arXiv2015

Understanding Functional Protein-Protein Interactions Of ABCB11 And ADA In Human And Mouse

Proteins are macromolecules which hardly act alone; they need to make interactions with some other proteins to do so. Numerous factors are there which can regulate the interactions between proteins [4]. Here in this present study we aim to understand Protein -Protein Interactions (PPIs) of two proteins ABCB11 and ADA from quantitative point of view. One of our major aims also is to study the factors that regulate the PPIs and thus to distinguish these PPIs with proper quantification across the two species Homo Sapiens and Mus Musculus respectively to know how one protein interacts with different set of proteins in different species.

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arXiv2015

The burden of HIV in a Public Hospital in Johannesburg, South Africa

South Africa has the greatest number of people living with HIV in the world but the direct impact of this on the public health system has not been directly measured. Using data from the Chris Hani Baragwanath Hospital, the largest hospital in the Southern Hemisphere, collected between January 2006 and December 2009, we demonstrate directly the scale of the impact of HIV on mortality in health services in the pubic sector in South Africa. During the period under investigation 14,431 people died in the hospital's medical wards, an average of 11 deaths each day. Of those that died 64 per cent of men and 82 per cent of women were HIV positive. Between the ages of 30 and 40, 94 percent of men and 96 percent of women of those that died were HIV-positive. These data not only reflect the extraordinary mortality directly attributable to the epidemic of HIV but also the massive burden placed on the health services at a time when triple combination therapy was available and these HIV-related deaths could have been averted.

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arXiv2016

Hidden Thermodynamic Information in Protein Amino Acid Mutation Tables

We combine the standard 1992 20x20 substitution matrix based on block alignment, BLOSUM62, with the standard 1982 amino acid hydropathicity scale KD as well as the modern 2007 hydropathicity scale MZ, and compare the results. The 20-parameter KD and MZ hydropathicity scales have different thermodynamic character, corresponding to first and second order transitions. The KD and MZ comparisons show that the mutation rates reflect quantitative iteration of qualitative amino acid phobic and philic binary 2x10 properties that define quaternary 4x5 subgroups (but not quinary 5x4 subgroups), with the modern MZ bioinformatic scale giving much better results. The quaternary 5 mer MZ 4x5 subgroups are called mutons (Mu5).

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arXiv2015

Modeling Eating Behaviors: the Role of Environment and Positive Food Association Learning via a Ratatouille Effect

Eating behaviors among a large population of children are studied as a dynamic process driven by nonlinear interactions in the sociocultural school environment. The impact of food association learning on diet dynamics, inspired by a pilot study conducted among Arizona children in Pre-Kindergarten to 8th grades, is used to build simple population-level learning models. Qualitatively, mathematical studies are used to highlight the possible ramifications of instruction, learning in nutrition, and health at the community level. Model results suggest that nutrition education programs at the population-level have minimal impact on improving eating behaviors, findings that agree with prior field studies. Hence, the incorporation of food association learning may be a better strategy for creating resilient communities of healthy and non-healthy eaters. A \textit{Ratatouille} effect can be observed when food association learners become food preference learners, a potential sustainable behavioral change, which in turn, may impact the overall distribution of healthy eaters. In short, this work evaluates the effectiveness of population-level intervention strategies and the importance of institutionalizing nutrition programs that factor in economical, social, cultural, and environmental elements that mesh well with the norms and values in the community.

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arXiv2016

Multivariate information measures: a unification using Möbius operators on subset lattices

Information related measures are useful tools for multi variable data analysis, as measures of dependence among variables, and as descriptions of order in biological and physical systems. Information related measures, like marginal entropies, mutual / interaction / multi-information, have been used in a number of fields including descriptions of systems complexity and biological data analysis. The mathematical relationships among these measures are therefore of significant interest. Relations between common information measures include the duality relations based on Möbius inversion on lattices. These are the direct consequence of the symmetries of the lattices of the sets of variables (subsets ordered by inclusion). While the mathematical properties and relationships among these information-related measures are of significant interest, there has been, to our knowledge, no systematic examination of the full range of relationships and no unification of this diverse range of functions into a single formalism as we do here. In this paper we define operators on functions on these lattices based on the Möbius inversion idea that map the functions into one another (Möbius operators.) We show that these operators form a simple group isomorphic to the symmetric group S3. Relations among the set of functions on the lattice are transparently expressed in terms of the operator algebra, and, applied to the information measures, can be used to derive a wide range of relationships among measures. We describe a direct relation between sums of conditional log-likelihoods and previously defined dependency measures. The algebra is naturally generalized which yields more extensive relationships. This formalism provides a fundamental unification of information related measures, but isomorphism of all distributive lattices with the subset lattice implies broad potential application of these results.

cs.IT↗

arXiv2015

Chirality in a quaternionic representation of the genetic code

A quaternionic representation of the genetic code, previously reported by the authors, is updated in order to incorporate chirality of nucleotide bases and amino acids. The original representation assigns to each nucleotide base a prime integer quaternion of norm 7 and involves a function that associates with each codon, represented by three of these quaternions, another integer quaternion (amino acid type quaternion) in such a way that the essentials of the standard genetic code (particulaty its degeneration) are preserved. To show the advantages of such a quaternionic representation we have, in turn, associated with each amino acid of a given protein, besides of the type quaternion, another real one according to its order along the protein (order quaternion) and have designed an algorithm to go from the primary to the tertiary structure of the protein by using type and order quaternions. In this context, we incorporate chirality in our representation by observing that the set of eight integer quaternions of norm 7 can be partitioned into a pair of subsets of cardinality four each with their elements mutually conjugates and by putting they in correspondence one to one with the two sets of enantiomers (D and L) of the four nucleotide bases adenine, cytosine, guanine and uracil, respectively. Thus, guided by two diagrams proposed for the codes evolution, we define functions that in each case assign a L- (D-) amino acid type integer quaternion to the triplets of D- (L-) bases. The assignation is such that for a given D-amino acid, the associated integer quaternion is the conjugate of that one corresponding to the enantiomer L. The chiral type quaternions obtained for the amino acids are used, together with a common set of order quaternions, to describe the folding of the two classes, L and D, of homochiral proteins.

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arXiv2017

A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health

Drought threatens food and water security around the world, and this threat is likely to become more severe under climate change. High resolution predictive information can help farmers, water managers, and others to manage the effects of drought. We have created an open source tool to produce short-term forecasts of vegetation health at high spatial resolution, using data that are global in coverage. The tool automates downloading and processing Moderate Resolution Imaging Spectroradiometer (MODIS) datasets, and training gradient-boosted machine models on hundreds of millions of observations to predict future values of the Enhanced Vegetation Index. We compared the predictive power of different sets of variables (raw spectral MODIS data and Level-3 MODIS products) in two regions with distinct agro-ecological systems, climates, and cloud coverage: Sri Lanka and California. Our tool provides considerably greater predictive power on held-out datasets than simpler baseline models.

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arXiv2016

X-ray experiment provides a way to reveal the distinction between discrete and continuous conformation of myosin head

The corner stone of the classical model after Huxley and Simmons is supposition that a myosin head can reside only in several discrete states and irregularly jumps from one state to another. Until now, it has not been found a way to experimentally verify this supposition although confirmation or refutation of the existence of discrete states is crucial for the solution of myosin motor problem. Here I show that a set of equal myosin heads arranged equidistantly along an actin filament produce X-ray pattern which varies with the type of conformation. If the lever arms of all myosin heads reside in one and the same position (continuous conformation), all the heads have the same form-factor and equally scatter electromagnetic wave. In this case, only the geometric factor associated with a spatial ordering of the heads will determine the X-ray pattern. The situation changes if the average lever arm position is the same, but inherently every head can reside only in several diverse discrete states, hopping irregularly from one to another. In this case, the form-factors corresponding to distinct states are dissimilar, and the increments in phases of X-rays scattered by different heads are different as well. Inasmuch as every quantum of radiation interacts with the heads residing in different states, this results in additional interference and some peaks in the X-ray pattern should slacken or even extinct as compared with the pattern from the heads with the continuous-type conformation. The formulas describing both cases are compared in this article. In general, the distinction between X-ray patterns is insignificant, but they could be appreciably different at some stages of conformation process (respective lever arm position depends on the type of discrete model). Consequently, one can with luck attempt to find out this difference using a high-sensitive equipment.

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arXiv2026

Biological hierarchies emerged from natural characteristics of number theory

Ecologists have long debated whether biological communities are fundamentally continuous or composed of discrete units. Continuum views emphasize smooth compositional change and ambiguous boundaries, whereas classification-based approaches rely on discrete community types for analysis and management. We show how biological grouping, particularly species formation, can emerge from interactions among populations governed by number-theoretic structure. In our framework, a species is identified with a $p$-Sylow subgroup of a community occupying a single niche; this identification is suported by a topological analysis. We call the resulting framework the patch with zeta dominance (PzDom) model. We then examine the system's topological properties in detail and demonstrate that both hierarchical organization and temporal ordering are induced by a one-dimensional probability space endowed with an appropriate topology. To clarify the appearance of induced fractal structure and its relation to renormalization, we develop a theoretical account based on a new observation: the scaling parameters that play the role of magnetization analogs coincide exactly with the imaginary parts of the nontrivial zeros of the Riemann zeta function. In the PzDom model, all required computations reduce to the time-dependent density of individuals. The PzDom framework reconciles these perspectives by showing that continuous community variation, represented by small $s$, can give rise to discrete species-level structure when number-theoretic constraints stabilize specific configurations. Thus, continuity and discreteness emerge as different dynamical phases of the same system, offering a unified explanation for long-standing debates in community ecology and the **species problem**.

q-bio.OT↗

arXiv2016

Extracellular stimulation of nerve cells with electric current spikes induced by voltage steps

A new stimulation paradigm is presented for the stimulation of nerve cells by extracellular electric currents. In the new paradigm stimulation is achieved with the current spike induced by a voltage step whenever the voltage step is applied to a live biological tissue. By experimental evidence and theoretical arguments, it is shown that this spike is well suited for the stimulation of nerve cells. Stimulation of the human tongue is used for proof of principle. Charge injection thresholds are measured for various voltages. The time-profile of the current spike used in the experiment has a half-width of about 1 microsecond. The decay of the spike is non-exponential. The spike has at least three distinctly different phases. A Maxwell phase is followed by a charge-rearrangement phase. Charging of cell membranes is completed in a third phase. All three phases contribute to depolarization or hyperpolarization of cell membranes. Due to the short duration of the spike the charge transfer is very small. The activation time (time of no return) of nerve cell membranes leading to an action potential is measured and found to be unexpectedly short. It can become as short as 3 microseconds for a voltage step of 10 V or higher.

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