Assembling genes from predicted exons in linear time with dynamic programming

In a number of programs for gene structure prediction in higher eukaryotic genomic sequences, exon prediction is decoupled from gene assembly: a large pool of candidate exons is predicted and scored from features located in the query DNA sequence, and candidate genes are assembled from such a pool as sequences of nonoverlapping frame-compatible exons. Genes are scored as a function of the scores of the assembled exons, and the highest scoring candidate gene is assumed to be the most likely gene encoded by the query DNA sequence. Considering additive gene scoring functions, currently available algorithms to determine such a highest scoring candidate gene run in time proportional to the square of the number of predicted exons. Here, we present an algorithm whose running time grows only linearly with the size of the set of predicted exons. Polynomial algorithms rely on the fact that, while scanning the set of predicted exons, the highest scoring gene ending in a given exon can be obtained by appending the exon to the highest scoring among the highest scoring genes ending at each compatible preceding exon. The algorithm here relies on the simple fact that such highest scoring gene can be stored and updated. This requires scanning the set of predicted exons simultaneously by increasing acceptor and donor position. On the other hand, the algorithm described here does not assume an underlying gene structure model. Indeed, the definition of valid gene structures is externally defined in the so-called Gene Model. The Gene Model specifies simply which gene features are allowed immediately upstream which other gene features in valid gene structures. This allows for great flexibility in formulating the gene identification problem. In particular it allows for multiple-gene two-strand predictions and for considering gene features other than coding exons (such as promoter elements) in valid gene structures.

Generation of induced pluripotent stem cells from human cord blood cells with only two factors:OCT4 and SOX2

Induced pluripotent stem cells (iPSC ) provide an invaluable resource for regenerative medicine as they allow the generationof patient-specific progenitors with potential value for cell therapy. However, in many instances, an off-the-shelf approach isdesirable, such as for cell therapy of acute conditions or when the patient’s somatic cells are altered as a consequence of a chronicdisease or aging. Cord blood (CB) stem cells appear ideally suited for this purpose as they are young cells expected to carryminimal somatic mutations and possess the immunological immaturity of newborn cells; additionally, several hundred thousandimmunotyped CB units are readily available through a worldwide network of CB banks. Here we present a detailed protocol for thederivation of CB stem cells and how they can be reprogrammed to pluripotency by retroviral transduction with only two factors(OCT 4 and SO X2) in 2 weeks and without the need for additional chemical compounds.

EGASP: the human ENCODE Genome Annotation Assessment Project

Background: We present the results of EGASP, a community experiment to assess the state-ofthe-art in genome annotation within the ENCODE regions, which span 1% of the human genomesequence. The experiment had two major goals: the assessment of the accuracy of computationalmethods to predict protein coding genes; and the overall assessment of the completeness of thecurrent human genome annotations as represented in the ENCODE regions. For thecomputational prediction assessment, eighteen groups contributed gene predictions. Weevaluated these submissions against each other based on a ‘reference set’ of annotationsgenerated as part of the GENCODE project. These annotations were not available to theprediction groups prior to the submission deadline, so that their predictions were blind and anexternal advisory committee could perform a fair assessment.Results: The best methods had at least one gene transcript correctly predicted for close to 70%of the annotated genes. Nevertheless, the multiple transcript accuracy, taking into accountalternative splicing, reached only approximately 40% to 50% accuracy. At the coding nucleotidelevel, the best programs reached an accuracy of 90% in both sensitivity and specificity. Programsrelying on mRNA and protein sequences were the most accurate in reproducing the manuallycurated annotations. Experimental validation shows that only a very small percentage (3.2%) of the selected 221 computationally predicted exons outside of the existing annotation could beverified.Conclusions: This is the first such experiment in human DNA, and we have followed thestandards established in a similar experiment, GASP1, in Drosophila melanogaster. We believe theresults presented here contribute to the value of ongoing large-scale annotation projects and shouldguide further experimental methods when being scaled up to the entire human genome sequence.

A two-stage approach for tonic identification in indian art music

In this paper we propose a new approach for tonic identification in Indian art music and present a proposal for acomplete iterative system for the same. Our method splits the task of tonic pitch identification into two stages. In the first stage, which is applicable to both vocal and instrumental music, we perform a multi-pitch analysis of the audio signal to identify the tonic pitch-class. Multi-pitch analysisallows us to take advantage of the drone sound, which constantlyreinforces the tonic. In the second stage we estimate the octave in which the tonic of the singer lies and is thusneeded only for the vocal performances. We analyse the predominant melody sung by the lead performer in order to establish the tonic octave. Both stages are individually evaluated on a sizable music collection and are shown toobtain a good accuracy. We also discuss the types of errors made by the method.Further, we present a proposal for a system that aims to incrementally utilize all the available data, both audio and metadata in order to identify the tonic pitch. It produces a tonic estimate and a confidence value, and is iterative in nature. At each iteration, more data is fed into the systemuntil the confidence value for the identified tonic is above a defined threshold. Rather than obtain high overall accuracy for our complete database, ultimately our goal is to develop a system which obtains very high accuracy on a subset of the database with maximum confidence.

What is the value of joint processing of pilots and data in block-fading channels?

The spectral efficiency achievable with joint processing of pilot and data symbol observations is compared with that achievable through the conventional (separate) approach of first estimating the channel on the basis of the pilot symbols alone, and subsequently detecting the datasymbols. Studied on the basis of a mutual information lower bound, joint processing is found to provide a non-negligible advantage relative to separate processing, particularly for fast fading. It is shown that, regardless of the fading rate, only a very small number of pilot symbols (at most one per transmit antenna and per channel coherence interval) shouldbe transmitted if joint processing is allowed.

Book vs. Fair Value Accounting in Banking, and Intertemporal Smoothing

The aim of this paper is to examine the pros and cons of book and fair value accounting from the perspective of the theory of banking. We consider the implications of the two accounting methods in an overlapping generations environment. As observed by Allen and Gale(1997), in an overlapping generation model, banks have a role as intergenerational connectors as they allow for intertemporal smoothing. Our main result is that when dividends depend on profits, book value ex ante dominates fair value, as it provides better intertemporal smoothing. This is in contrast with the standard view that states that, fair value yields a better allocation as it reflects the real opportunity cost of assets. Banking regulation play an important role by providing the right incentives for banks to smooth intertemporal consumption whereas market discipline improves intratemporal efficiency.

Ecologies of Value in a Wall Street Trading Room

Our task in this paper is to analyze the organization of trading in the era of quantitative finance. To do so, we conduct an ethnography of arbitrage, the trading strategy that best exemplifies finance in the wake of the quantitative revolution. In contrast to value and momentum investing, we argue, arbitrage involves an art of association-the construction of equivalence (comparability) of properties across different assets. In place of essential or relational characteristics, the peculiar valuation that takes place in arbitrage is based on an operation that makes something the measure of something else-associating securities to each other. The process of recognizing opportunities and the practices of making novel associations are shaped by the specific socio-spatial and socio-technical configurations of the trading room. Calculation is distributed across persons and instruments as the trading room organizes interaction among diverse principles of valuation.

Weak and Strong Altruism in Trait Groups: Reproductive Suicide, Personal Fitness, and Expected Value

A simple variant of trait group selection, employing predators as the mechanism underlying group selection, supports contingent reproductive suicide as altruism (i.e., behavior lowering personal fitness while augmenting that of another) without kin assortment. The contingent suicidal type may either saturate the population or be polymorphic with a type avoiding suicide, depending on parameters. In addition to contingent suicide, this randomly assorting morph may also exhibit continuously expressed strong altruism (sensu Wilson 1979) usually thought restricted to kin selection. The model will not, however, support a sterile worker caste as such, where sterility occurs before life history events associated with effective altruism; reproductive suicide must remain fundamentally contingent (facultative sensu West Eberhard 1987; Myles 1988) under random assortment. The continuously expressed strong altruism supported by the model may be reinterpreted as probability of arbitrarily committing reproductive suicide, without benefit for another; such arbitrary suicide (a "load" on "adaptive" suicide) is viable only under a more restricted parameter space relative to the necessarily concomitant adaptive contingent suicide.

Hipotecats a la crisi: passat, present i futur de la crisi

Treball de recerca realitzat per un alumne d’ensenyament secundari i guardonat amb un Premi CIRIT per fomentar l'esperit científic del Jovent l’any 2010. Els objectius del treball són, entre d'altres, una explicació de la crisi actual, juntament amb les causes tant llunyanes com pròximes i els detonants. Alhora un comparació de crisis, sobretot amb el Crac del 29. També hi ha una intenció de previsió dels propers anys de crisi, i alhora a llarg termini. A partir de la part explicada anteriorment, creació d'un projecte de futur per a la previsió de futures crisis econòmiques. Finalment, diverses enquestes per a saber què i quan en sap la gent del tema i diferents entrevistes a coneguts economistes per tenir punts de vista experts.

A subsampling approach to estimating the distribution of diversing statistics with application to assessing financial market risks

In this paper we propose a subsampling estimator for the distribution ofstatistics diverging at either known rates when the underlying timeseries in strictly stationary abd strong mixing. Based on our results weprovide a detailed discussion how to estimate extreme order statisticswith dependent data and present two applications to assessing financialmarket risk. Our method performs well in estimating Value at Risk andprovides a superior alternative to Hill's estimator in operationalizingSafety First portofolio selection.

The value of useless information

There are many situations in which individuals have a choice of whether or notto observe eventual outcomes. In these instances, individuals often prefer to remainignorant. These contexts are outside the scope of analysis of the standard vonNeumann-Morgenstern (vNM) expected utility model, which does not distinguishbetween lotteries for which the agent sees the final outcome and those for which hedoes not. I develop a simple model that admits preferences for making an observationor for remaining in doubt. I then use this model to analyze the connectionbetween preferences of this nature and risk-attitude. This framework accommodatesa wide array of behavioral patterns that violate the vNM model, and thatmay not seem related, prima facie. For instance, it admits self-handicapping, inwhich an agent chooses to impair his own performance. It also accommodatesa status quo bias without having recourse to framing effects, or to an explicitdefinition of reference points. In a political economy context, voters have strictincentives to shield themselves from information. In settings with other-regardingpreferences, this model predicts observed behavior that seems inconsistent witheither altruism or self-interested behavior.

Two-sided learning in New Keynesian models: Dynamics, (lack of) convergence and the value of information

This paper investigates the role of learning by private agents and the central bank(two-sided learning) in a New Keynesian framework in which both sides of the economyhave asymmetric and imperfect knowledge about the true data generating process. Weassume that all agents employ the data that they observe (which may be distinct fordifferent sets of agents) to form beliefs about unknown aspects of the true model ofthe economy, use their beliefs to decide on actions, and revise these beliefs througha statistical learning algorithm as new information becomes available. We study theshort-run dynamics of our model and derive its policy recommendations, particularlywith respect to central bank communications. We demonstrate that two-sided learningcan generate substantial increases in volatility and persistence, and alter the behaviorof the variables in the model in a significant way. Our simulations do not convergeto a symmetric rational expectations equilibrium and we highlight one source thatinvalidates the convergence results of Marcet and Sargent (1989). Finally, we identifya novel aspect of central bank communication in models of learning: communicationcan be harmful if the central bank's model is substantially mis-specified.

Book vs. fair value accounting in banking and intertemporal smoothing

The aim of this paper is to examine the pros and cons of book and fair value accounting from the perspective of the theory of banking. We consider the implications of the two accounting methods in an overlapping generations environment. As observed by Allen and Gale(1997), in an overlapping generation model, banks have a role as intergenerational connectors as they allow for intertemporal smoothing. Our main result is that when dividends depend on profits, book value ex ante dominates fair value, as it provides better intertemporal smoothing. This is in contrast with the standard view that states that, fair value yields a better allocation as it reflects the real opportunity cost of assets. Banking regulation play an important role by providing the right incentives for banks to smooth intertemporal consumption whereas market discipline improves intratemporal efficiency.