Showing papers by "Massachusetts Institute of Technology published in 2005"

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

Abstract: Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

Haploview: analysis and visualization of LD and haplotype maps

Abstract: Summary: Research over the last few years has revealed significant haplotype structure in the human genome. The characterization of these patterns, particularly in the context of medical genetic association studies, is becoming a routine research activity. Haploview is a software package that provides computation of linkage disequilibrium statistics and population haplotype patterns from primary genotype data in a visually appealing and interactive interface. Availability: http://www.broad.mit.edu/mpg/haploview/ Contact: jcbarret@broad.mit.edu

MicroRNA expression profiles classify human cancers

Abstract: Recent work has revealed the existence of a class of small non-coding RNA species, known as microRNAs (miRNAs), which have critical functions across various biological processes. Here we use a new, bead-based flow cytometric miRNA expression profiling method to present a systematic expression analysis of 217 mammalian miRNAs from 334 samples, including multiple human cancers. The miRNA profiles are surprisingly informative, reflecting the developmental lineage and differentiation state of the tumours. We observe a general downregulation of miRNAs in tumours compared with normal tissues. Furthermore, we were able to successfully classify poorly differentiated tumours using miRNA expression profiles, whereas messenger RNA profiles were highly inaccurate when applied to the same samples. These findings highlight the potential of miRNA profiling in cancer diagnosis.

The Design and Implementation of FFTW3

Abstract: FFTW is an implementation of the discrete Fourier transform (DFT) that adapts to the hardware in order to maximize performance. This paper shows that such an approach can yield an implementation that is competitive with hand-optimized libraries, and describes the software structure that makes our current FFTW3 version flexible and adaptive. We further discuss a new algorithm for real-data DFTs of prime size, a new way of implementing DFTs by means of machine-specific single-instruction, multiple-data (SIMD) instructions, and how a special-purpose compiler can derive optimized implementations of the discrete cosine and sine transforms automatically from a DFT algorithm.

Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs

Abstract: MicroRNAs (miRNAs) are a class of noncoding RNAs that post-transcriptionally regulate gene expression in plants and animals. To investigate the influence of miRNAs on transcript levels, we transfected miRNAs into human cells and used microarrays to examine changes in the messenger RNA profile. Here we show that delivering miR-124 causes the expression profile to shift towards that of brain, the organ in which miR-124 is preferentially expressed, whereas delivering miR-1 shifts the profile towards that of muscle, where miR-1 is preferentially expressed. In each case, about 100 messages were downregulated after 12 h. The 3' untranslated regions of these messages had a significant propensity to pair to the 5' region of the miRNA, as expected if many of these messages are the direct targets of the miRNAs. Our results suggest that metazoan miRNAs can reduce the levels of many of their target transcripts, not just the amount of protein deriving from these transcripts. Moreover, miR-1 and miR-124, and presumably other tissue-specific miRNAs, seem to downregulate a far greater number of targets than previously appreciated, thereby helping to define tissue-specific gene expression in humans.

Detection of the baryon acoustic peak in the large-scale correlation function of SDSS luminous red galaxies

Abstract: We present the large-scale correlation function measured from a spectroscopic sample of 46,748 luminous red galaxies from the Sloan Digital Sky Survey. The survey region covers 0.72h −3 Gpc 3 over 3816 square degrees and 0.16 < z < 0.47, making it the best sample yet for the study of large-scale structure. We find a well-detected peak in the correlation function at 100h −1 Mpc separation that is an excellent match to the predicted shape and location of the imprint of the recombination-epoch acoustic oscillations on the low-redshift clustering of matter. This detection demonstrates the linear growth of structure by gravitational instability between z ≈ 1000 and the present and confirms a firm prediction of the standard cosmological theory. The acoustic peak provides a standard ruler by which we can measure the ratio of the distances to z = 0.35 and z = 1089 to 4% fractional accuracy and the absolute distance to z = 0.35 to 5% accuracy. From the overall shape of the correlation function, we measure the matter density mh 2 to 8% and find agreement with the value from cosmic microwave background (CMB) anisotropies. Independent of the constraints provided by the CMB acoustic scale, we find m = 0.273 ±0.025+0.123(1+ w0)+0.137K. Including the CMB acoustic scale, we find that the spatial curvature is K = −0.010 ± 0.009 if the dark energy is a cosmological constant. More generally, our results provide a measurement of cosmological distance, and hence an argument for dark energy, based on a geometric method with the same simple physics as the microwave background anisotropies. The standard cosmological model convincingly passes these new and robust tests of its fundamental properties. Subject headings: cosmology: observations — large-scale structure of the universe — distance scale — cosmological parameters — cosmic microwave background — galaxies: elliptical and lenticular, cD

Cognitive Reflection and Decision Making

Abstract: This paper introduces a three-item "Cognitive Reflection Test" (CRT) as a simple measure of one type of cognitive ability—the ability or disposition to reflect on a question and resist reporting the first response that comes to mind. The author will show that CRT scores are predictive of the types of choices that feature prominently in tests of decision-making theories, like expected utility theory and prospect theory. Indeed, the relation is sometimes so strong that the preferences themselves effectively function as expressions of cognitive ability—an empirical fact begging for a theoretical explanation. The author examines the relation between CRT scores and two important decision-making characteristics: time preference and risk preference. The CRT scores are then compared with other measures of cognitive ability or cognitive "style." The CRT scores exhibit considerable difference between men and women and the article explores how this relates to sex differences in time and risk preferences. The final section addresses the interpretation of correlations between cognitive abilities and decision-making characteristics.

Increasing destructiveness of tropical cyclones over the past 30 years

Abstract: Theory and modelling predict that hurricane intensity should increase with increasing global mean temperatures, but work on the detection of trends in hurricane activity has focused mostly on their frequency and shows no trend. Here I define an index of the potential destructiveness of hurricanes based on the total dissipation of power, integrated over the lifetime of the cyclone, and show that this index has increased markedly since the mid-1970s. This trend is due to both longer storm lifetimes and greater storm intensities. I find that the record of net hurricane power dissipation is highly correlated with tropical sea surface temperature, reflecting well-documented climate signals, including multi-decadal oscillations in the North Atlantic and North Pacific, and global warming. My results suggest that future warming may lead to an upward trend in tropical cyclone destructive potential, and--taking into account an increasing coastal population--a substantial increase in hurricane-related losses in the twenty-first century.

Cellular processing of platinum anticancer drugs.

Abstract: Cisplatin, carboplatin and oxaliplatin are platinum-based drugs that are widely used in cancer chemotherapy. Platinum–DNA adducts, which are formed following uptake of the drug into the nucleus of cells, activate several cellular processes that mediate the cytotoxicity of these platinum drugs. This review focuses on recently discovered cellular pathways that are activated in response to cisplatin, including those involved in regulating drug uptake, the signalling of DNA damage, cell-cycle checkpoints and arrest, DNA repair and cell death. Such knowledge of the cellular processing of cisplatin adducts with DNA provides valuable clues for the rational design of more efficient platinum-based drugs as well as the development of new therapeutic strategies.

Genome-wide association studies for common diseases and complex traits

Abstract: Genetic factors strongly affect susceptibility to common diseases and also influence disease-related quantitative traits. Identifying the relevant genes has been difficult, in part because each causal gene only makes a small contribution to overall heritability. Genetic association studies offer a potentially powerful approach for mapping causal genes with modest effects, but are limited because only a small number of genes can be studied at a time. Genome-wide association studies will soon become possible, and could open new frontiers in our understanding and treatment of disease. However, the execution and analysis of such studies will require great care.

Pictorial Structures for Object Recognition

Abstract: In this paper we present a computationally efficient framework for part-based modeling and recognition of objects. Our work is motivated by the pictorial structure models introduced by Fischler and Elschlager. The basic idea is to represent an object by a collection of parts arranged in a deformable configuration. The appearance of each part is modeled separately, and the deformable configuration is represented by spring-like connections between pairs of parts. These models allow for qualitative descriptions of visual appearance, and are suitable for generic recognition problems. We address the problem of using pictorial structure models to find instances of an object in an image as well as the problem of learning an object model from training examples, presenting efficient algorithms in both cases. We demonstrate the techniques by learning models that represent faces and human bodies and using the resulting models to locate the corresponding objects in novel images.

Energy scavenging for mobile and wireless electronics

Abstract: Energy harvesting has grown from long-established concepts into devices for powering ubiquitously deployed sensor networks and mobile electronics. Systems can scavenge power from human activity or derive limited energy from ambient heat, light, radio, or vibrations. Ongoing power management developments enable battery-powered electronics to live longer. Such advances include dynamic optimization of voltage and clock rate, hybrid analog-digital designs, and clever wake-up procedures that keep the electronics mostly inactive. Exploiting renewable energy resources in the device's environment, however, offers a power source limited by the device's physical survival rather than an adjunct energy store. Energy harvesting's true legacy dates to the water wheel and windmill, and credible approaches that scavenge energy from waste heat or vibration have been around for many decades. Nonetheless, the field has encountered renewed interest as low-power electronics, wireless standards, and miniaturization conspire to populate the world with sensor networks and mobile devices. This article presents a whirlwind survey through energy harvesting, spanning historic and current developments.

Genome sequence, comparative analysis and haplotype structure of the domestic dog

Abstract: Here we report a high-quality draft genome sequence of the domestic dog (Canis familiaris), together with a dense map of single nucleotide polymorphisms (SNPs) across breeds. The dog is of particular interest because it provides important evolutionary information and because existing breeds show great phenotypic diversity for morphological, physiological and behavioural traits. We use sequence comparison with the primate and rodent lineages to shed light on the structure and evolution of genomes and genes. Notably, the majority of the most highly conserved non-coding sequences in mammalian genomes are clustered near a small subset of genes with important roles in development. Analysis of SNPs reveals long-range haplotypes across the entire dog genome, and defines the nature of genetic diversity within and across breeds. The current SNP map now makes it possible for genome-wide association studies to identify genes responsible for diseases and traits, with important consequences for human and companion animal health.

Complete Replication of Hepatitis C Virus in Cell Culture

Abstract: Many aspects of the hepatitis C virus (HCV) life cycle have not been reproduced in cell culture, which has slowed research progress on this important human pathogen. Here, we describe a full-length HCV genome that replicates and produces virus particles that are infectious in cell culture (HCVcc). Replication of HCVcc was robust, producing nearly 10(5) infectious units per milliliter within 48 hours. Virus particles were filterable and neutralized with a monoclonal antibody against the viral glycoprotein E2. Viral entry was dependent on cellular expression of a putative HCV receptor, CD81. HCVcc replication was inhibited by interferon-alpha and by several HCV-specific antiviral compounds, suggesting that this in vitro system will aid in the search for improved antivirals.

A sparse signal reconstruction perspective for source localization with sensor arrays

Abstract: We present a source localization method based on a sparse representation of sensor measurements with an overcomplete basis composed of samples from the array manifold. We enforce sparsity by imposing penalties based on the /spl lscr//sub 1/-norm. A number of recent theoretical results on sparsifying properties of /spl lscr//sub 1/ penalties justify this choice. Explicitly enforcing the sparsity of the representation is motivated by a desire to obtain a sharp estimate of the spatial spectrum that exhibits super-resolution. We propose to use the singular value decomposition (SVD) of the data matrix to summarize multiple time or frequency samples. Our formulation leads to an optimization problem, which we solve efficiently in a second-order cone (SOC) programming framework by an interior point implementation. We propose a grid refinement method to mitigate the effects of limiting estimates to a grid of spatial locations and introduce an automatic selection criterion for the regularization parameter involved in our approach. We demonstrate the effectiveness of the method on simulated data by plots of spatial spectra and by comparing the estimator variance to the Crame/spl acute/r-Rao bound (CRB). We observe that our approach has a number of advantages over other source localization techniques, including increased resolution, improved robustness to noise, limitations in data quantity, and correlation of the sources, as well as not requiring an accurate initialization.

HSP90 and the chaperoning of cancer.

Abstract: Standing watch over the proteome, molecular chaperones are an ancient and evolutionarily conserved class of proteins that guide the normal folding, intracellular disposition and proteolytic turnover of many of the key regulators of cell growth, differentiation and survival. This essential guardian function is subverted during oncogenesis to allow malignant transformation and to facilitate rapid somatic evolution. Pharmacologically 'bribing' the essential guard duty of the chaperone HSP90 (heat-shock protein of 90 kDa) seems to offer a unique anticancer strategy of considerable promise.

Engineering Design Thinking, Teaching, and Learning

Abstract: This paper is based on the premises that the purpose of engineering education is to graduate engineers who can design, and that design thinking is complex. The paper begins by briefly reviewing the history and role of design in the engineering curriculum. Several dimensions of design thinking are then detailed, explaining why design is hard to learn and harder still to teach, and outlining the research available on how well design thinking skills are learned. The currently most-favored pedagogical model for teaching design, project-based learning (PBL), is explored next, along with available assessment data on its success. Two contexts for PBL are emphasized: first-year cornerstone courses and globally dispersed PBL courses. Finally, the paper lists some of the open research questions that must be answered to identify the best pedagogical practices of improving design learning, after which it closes by making recommendations for research aimed at enhancing design learning.

TinyDB: an acquisitional query processing system for sensor networks

Abstract: We discuss the design of an acquisitional query processor for data collection in sensor networks. Acquisitional issues are those that pertain to where, when, and how often data is physically acquired (sampled) and delivered to query processing operators. By focusing on the locations and costs of acquiring data, we are able to significantly reduce power consumption over traditional passive systems that assume the a priori existence of data. We discuss simple extensions to SQL for controlling data acquisition, and show how acquisitional issues influence query optimization, dissemination, and execution. We evaluate these issues in the context of TinyDB, a distributed query processor for smart sensor devices, and show how acquisitional techniques can provide significant reductions in power consumption on our sensor devices.

Beyond Continuity: Institutional Change in Advanced Political Economies

Abstract: Debates surrounding institutional change have become increasingly central to Political Science, Management Studies, and Sociology, opposing the role of globalization in bringing about a convergence of national economies and institutions on one model to theories about 'Varieties of Capitalism'. This book brings together a distinguished set of contributors from a variety of disciplines to examine current theories of institutional change. The chapters highlight the limitations of these theories, finding them lacking in the analytic tools necessary to identify the changes occurring at a national level, and therefore tend to explain many changes and innovation as simply another version of previous situations. Instead a model emerges of contemporary political economies developing in incremental but cumulatively transformative processes. The contributors show that a wide, but not infinite, variety of models of institutional change exist which can meaningfully distinguished and analytically compared. They offer an empirically grounded typology of modes of institutional change that offer important insights on mechanisms of social and political stability, and evolution generally. Beyond Continuity provides a more complex and fundamental understanding of institutional change, and will be important reading for academics, researchers, and advanced students of Political Science, Management Studies, Sociology, and Economics.

Systematic discovery of regulatory motifs in human promoters and 3′ UTRs by comparison of several mammals

Abstract: Comprehensive identification of all functional elements encoded in the human genome is a fundamental need in biomedical research. Here, we present a comparative analysis of the human, mouse, rat and dog genomes to create a systematic catalogue of common regulatory motifs in promoters and 3' untranslated regions (3' UTRs). The promoter analysis yields 174 candidate motifs, including most previously known transcription-factor binding sites and 105 new motifs. The 3'-UTR analysis yields 106 motifs likely to be involved in post-transcriptional regulation. Nearly one-half are associated with microRNAs (miRNAs), leading to the discovery of many new miRNA genes and their likely target genes. Our results suggest that previous estimates of the number of human miRNA genes were low, and that miRNAs regulate at least 20% of human genes. The overall results provide a systematic view of gene regulation in the human, which will be refined as additional mammalian genomes become available.

Constructing free-energy approximations and generalized belief propagation algorithms

Abstract: Important inference problems in statistical physics, computer vision, error-correcting coding theory, and artificial intelligence can all be reformulated as the computation of marginal probabilities on factor graphs. The belief propagation (BP) algorithm is an efficient way to solve these problems that is exact when the factor graph is a tree, but only approximate when the factor graph has cycles. We show that BP fixed points correspond to the stationary points of the Bethe approximation of the free energy for a factor graph. We explain how to obtain region-based free energy approximations that improve the Bethe approximation, and corresponding generalized belief propagation (GBP) algorithms. We emphasize the conditions a free energy approximation must satisfy in order to be a "valid" or "maxent-normal" approximation. We describe the relationship between four different methods that can be used to generate valid approximations: the "Bethe method", the "junction graph method", the "cluster variation method", and the "region graph method". Finally, we explain how to tell whether a region-based approximation, and its corresponding GBP algorithm, is likely to be accurate, and describe empirical results showing that GBP can significantly outperform BP.

Light-induced shape-memory polymers

Abstract: Materials are said to show a shape-memory effect if they can be deformed and fixed into a temporary shape, and recover their original, permanent shape only on exposure to an external stimulus. Shape-memory polymers have received increasing attention because of their scientific and technological significance. In principle, a thermally induced shape-memory effect can be activated by an increase in temperature (also obtained by heating on exposure to an electrical current or light illumination). Several papers have described light-induced changes in the shape of polymers and gels, such as contraction, bending or volume changes. Here we report that polymers containing cinnamic groups can be deformed and fixed into pre-determined shapes--such as (but not exclusively) elongated films and tubes, arches or spirals--by ultraviolet light illumination. These new shapes are stable for long time periods, even when heated to 50 degrees C, and they can recover their original shape at ambient temperatures when exposed to ultraviolet light of a different wavelength. The ability of polymers to form different pre-determined temporary shapes and subsequently recover their original shape at ambient temperatures by remote light activation could lead to a variety of potential medical and other applications.