• A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection

      Fourati, S; Talla, A; Mahmoudian, M; Burkhart, JG; Klén, R; Henao, R; Yu, T; Aydın, Z; Yeung, KY; Ahsen, ME; Almugbel, R; Jahandideh, S; Liang, X; Nordling, TEM; Shiga, M; Stanescu, A; Vogel, R; Abdallah, EB; Aghababazadeh, FA; Amadoz, A; Bhalla, S; Bleakley, K; Bongen, E; Borzacchielo, D; Bucher, P; Carbonell-Caballero, J; Chaudhary, K; Chinesta, F; Chodavarapu, P; Chow, RD; Cokelaer, T; Cubuk, C; Dhanda, SK; Dopazo, J; Faux, T; Feng, Y; Flinta, C; Guziolowski, C; He, D; Hidalgo, MR; Hou, J; Inoue, K; Jaakkola, MK; Ji, J; Kumar, R; Kumar, S; Kursa, MB; Li, Q; Łopuszyński, M; Lu, P; Magnin, M; Mao, W; Miannay, B; Nikolayeva, I; Obradovic, Z; Pak, C; Rahman, MM; Razzaq, M; Ribeiro, T; Roux, O; Saghapour, E; Saini, H; Sarhadi, S; Sato, H; Schwikowski, B; Sharma, A; Sharma, R; Singla, D; Stojkovic, I; Suomi, T; Suprun, M; Tian, C; Tomalin, LE; Xie, L; Yu, X; Pandey, G; Chiu, C; McClain, MT; Woods, CW; Ginsburg, GS; Elo, LL; Tsalik, EL; Mangravite, LM; Sieberts, SK (2018-12-01)
      © 2018, The Author(s). The response to respiratory viruses varies substantially between individuals, and there are currently no known molecular predictors from the early stages of infection. Here we conduct a community-based analysis to determine whether pre- or early post-exposure molecular factors could predict physiologic responses to viral exposure. Using peripheral blood gene expression profiles collected from healthy subjects prior to exposure to one of four respiratory viruses (H1N1, H3N2, Rhinovirus, and RSV), as well as up to 24 h following exposure, we find that it is possible to construct models predictive of symptomatic response using profiles even prior to viral exposure. Analysis of predictive gene features reveal little overlap among models; however, in aggregate, these genes are enriched for common pathways. Heme metabolism, the most significantly enriched pathway, is associated with a higher risk of developing symptoms following viral exposure. This study demonstrates that pre-exposure molecular predictors can be identified and improves our understanding of the mechanisms of response to respiratory viruses.
    • A cyclic nucleotide-gated channel mutation associated with canine daylight blindness provides insight into a role for the S2 segment Tri-Asp motif in channel biogenesis

      Tanaka, N; Delemotte, L; Klein, ML; Komáromy, AM; Tanaka, JC (2014-02-21)
      Cone cyclic nucleotide-gated channels are tetramers formed by CNGA3 and CNGB3 subunits; CNGA3 subunits function as homotetrameric channels but CNGB3 exhibits channel function only when co-expressed with CNGA3. An aspartatic acid (Asp) to asparagine (Asn) missense mutation at position 262 in the canine CNGB3 (D262N) subunit results in loss of cone function (daylight blindness), suggesting an important role for this aspartic acid residue in channel biogenesis and/or function. Asp 262 is located in a conserved region of the second transmembrane segment containing three Asp residues designated the Tri-Asp motif. This motif is conserved in all CNG channels. Here we examine mutations in canine CNGA3 homomeric channels using a combination of experimental and computational approaches. Mutations of these conserved Asp residues result in the absence of nucleotide-activated currents in heterologous expression. A fluorescent tag on CNGA3 shows mislocalization of mutant channels. Co-expressing CNGB3 Tri-Asp mutants with wild type CNGA3 results in some functional channels, however, their electrophysiological characterization matches the properties of homomeric CNGA3 channels. This failure to record heteromeric currents suggests that Asp/Asn mutations affect heteromeric subunit assembly. A homology model of S1-S6 of the CNGA3 channel was generated and relaxed in a membrane using molecular dynamics simulations. The model predicts that the Tri-Asp motif is involved in non-specific salt bridge pairings with positive residues of S3/S4. We propose that the D262N mutation in dogs with CNGB3-day blindness results in the loss of these inter-helical interactions altering the electrostatic equilibrium within in the S1-S4 bundle. Because residues analogous to Tri-Asp in the voltage-gated Shaker potassium channel family were implicated in monomer folding, we hypothesize that destabilizing these electrostatic interactions impairs the monomer folding state in D262N mutant CNG channels during biogenesis. © 2014 Tanaka et al.
    • A data-driven acute inflammation therapy

      Radosavljevic, V; Ristovski, K; Obradovic, Z (2013-11-25)
      Acute inflammation is a severe medical condition defined as an inflammatory response of the body to an infection. Its rapid progression requires quick and accurate decisions from clinicians. Inadequate and delayed decisions makes acute inflammation the 10th leading cause of death overall in United States with the estimated cost of treatment about $17 billion annually. However, despite the need, there are limited number of methods that could assist clinicians to determine optimal therapies for acute inflammation. We developed a data-driven method for suggesting optimal therapy by using machine learning model that is learned on historical patients' behaviors. To reduce both the risk of failure and the expense for clinical trials, our method is evaluated on a virtual patients generated by a mathematical model that emulates inflammatory response. In conducted experiments, acute inflammation was handled with two complimentary pro- and anti-inflammatory medications which adequate timing and doses are crucial for the successful outcome. Our experiments show that the dosage regimen assigned with our data-driven method significantly improves the percentage of healthy patients when compared to results by other methods used in clinical practice and found in literature. Our method saved 88% of patients that would otherwise die within a week, while the best method found in literature saved only 73% of patients. At the same time, our method used lower doses of medications than alternatives. In addition, our method achieved better results than alternatives when only incomplete or noisy measurements were available over time as well as it was less affected by therapy delay. The presented results provide strong evidence that models from the artificial intelligence community have a potential for development of personalized treatment strategies for acute inflammation. © 2013 Radosavljevic et al; licensee BioMed Central Ltd.
    • A decade of EGFR inhibition in EGFR-mutated non small cell lung cancer (NSCLC): Old successes and future perspectives

      Russo, A; Franchina, T; Ricciardi, GRR; Picone, A; Ferraro, G; Mariangela Zanghì; Toscano, G; Giordano, A; Adamo, V; Giordano, Antonio|0000-0002-5959-016X (2015-01-01)
      The discovery of Epidermal Growth Factor Receptor (EGFR) mutations in Non Small Cell Lung Cancer (NSCLC) launched the era of personalized medicine in advanced NSCLC, leading to a dramatic shift in the therapeutic landscape of this disease. After ten years from the individuation of activating mutations in the tyrosine kinase domain of the EGFR in NSCLC patients responding to the EGFR tyrosine kinase inhibitor (TKI) Gefitinib, several progresses have been done and first line treatment with EGFR TKIs is a firmly established option in advanced EGFR-mutated NSCLC patients. During the last decade, different EGFR TKIs have been developed and three inhibitors have been approved so far in these selected patients. However, despite great breakthroughs have been made, treatment of these molecularly selected patients poses novel therapeutic challenges, such as emerging of acquired resistance, brain metastases development or the need to translate these treatments in earlier clinical settings, such as adjuvant therapy. The aim of this paper is to provide a comprehensive review of the major progresses reported so far in the EGFR inhibition in this molecularly-selected subgroup of NSCLC patients, from the early successes with first generation EGFR TKIs, Erlotinib and Gefitinib, to the novel irreversible and mutant-selective inhibitors and ultimately the emerging challenges that we, in the next future, are called to deal with.
    • A Decade of Research on Social Media and Journalism: Assumptions, Blind Spots, and a Way Forward

      Lewis, Seth C.; Molyneux, Logan; 0000-0001-7382-3065 (2018-11-08)
      Amid a broader reckoning about the role of social media in public life, this article argues that the same scrutiny can be applied to the journalism studies field and its approaches to examining social media. A decade later, what hath such research wrought? In the broad study of news and its digital transformation, few topics have captivated researchers quite like social media, with hundreds of studies on everything from how journalists use Twitter, Facebook, Instagram, YouTube, and Snapchat to how such platforms facilitate various forms of engagement between journalists and audiences. Now, some 10 years into journalism studies on social media, we need a more particular accounting of the assumptions, biases, and blind spots that have crept into this line of research. Our purpose is to provoke reflection and chart a path for future research by critiquing themes of what has come before. In particular, our goal is to untangle three faulty assumptions—often implicit but no less influential—that have been overlooked in the rapid take-up of social media as a key phenomenon for journalism studies: (1) that social media would be a net positive; (2) that social media reflects reality; and (3) that social media matters over and above other factors.
    • A first look at ARFome: Dual-coding genes in mammalian genomes

      Chung, WY; Wadhawan, S; Szklarczyk, R; Pond, SK; Nekrutenko, A; Pond, Sergei L. Kosakovsky|0000-0003-4817-4029 (2007-05-01)
      Coding of multiple proteins by overlapping reading frames is not a feature one would associate with eukaryotic genes. Indeed, codependency between codons of overlapping protein-coding regions imposes a unique set of evolutionary constraints, making it a costly arrangement. Yet in cases of tightly coexpressed interacting proteins, dual coding may be advantageous. Here we show that although dual coding is nearly impossible by chance, a number of human transcripts contain overlapping coding regions. Using newly developed statistical techniques, we identified 40 candidate genes with evolutionarily conserved overlapping coding regions. Because our approach is conservative, we expect mammals to possess more dual-coding genes. Our results emphasize that the skepticism surrounding eukaryotic dual coding is unwarranted: rather than being artifacts, overlapping reading frames are often hallmarks of fascinating biology. © 2007 Chung et al.
    • A fog computing solution for context-based privacy leakage detection for android healthcare devices

      Gu, J; Huang, R; Jiang, L; Qiao, G; Du, X; Guizani, M; Du, Xiaojiang|0000-0003-4235-9671 (2019-03-01)
      © 2019 by the authors. Licensee MDPI, Basel, Switzerland. Intelligent medical service system integrates wireless internet of things (WIoT), including medical sensors, wireless communications, and middleware techniques, so as to collect and analyze patients’ data to examine their physical conditions by many personal health devices (PHDs) in real time. However, large amount of malicious codes on the Android system can compromise consumers’ privacy, and further threat the hospital management or even the patients’ health. Furthermore, this sensor-rich system keeps generating large amounts of data and saturates the middleware system. To address these challenges, we propose a fog computing security and privacy protection solution. Specifically, first, we design the security and privacy protection framework based on the fog computing to improve tele-health and tele-medicine infrastructure. Then, we propose a context-based privacy leakage detection method based on the combination of dynamic and static information. Experimental results show that the proposed method can achieve higher detection accuracy and lower energy consumption compared with other state-of-art methods.
    • A Functionalist Approach to Comparative Abortion Law

      Rebouché, Rachel (2014)
      This chapter critiques the present comparative methodology in abortion law and explores the possibilities of a new comparative approach. The current method relies on high-­ profile but dated constitutional abortion decisions from the United States and Germany. Courts continue to rely on these cases to justify their decisions as consistent with a modern, global convergence around women’s rights and to minimize national resistance to contested law reform. These comparisons, however, oversimplify legal developments of the past forty years by focusing on constitutional norms and legislative regimes, rather than on the relationship between abortion law and practice.
    • A generalized birth and death process for modeling the fates of gene duplication

      Zhao, J; Teufel, AI; Liberles, DA; Liu, L; Liberles, David A|0000-0003-3487-8826 (2015-12-08)
      © 2015 Zhao et al. Background: Accurately estimating the timing and mode of gene duplications along the evolutionary history of species can provide invaluable information about underlying mechanisms by which the genomes of organisms evolved and the genes with novel functions arose. Mechanistic models have previously been introduced that allow for probabilistic inference of the evolutionary mechanism for duplicate gene retention based upon the average rate of loss over time of the duplicate. However, there is currently no probabilistic model embedded in a birth-death modeling framework that can take into account the effects of different evolutionary mechanisms of gene retention when analyzing gene family data. Results: In this study, we describe a generalized birth-death process for modeling the fates of gene duplication. Use of mechanistic models in a phylogenetic framework requires an age-dependent birth-death process. Starting with a single population corresponding to the lineage of a phylogenetic tree and with an assumption of a clock that starts ticking for each duplicate at its birth, an age-dependent birth-death process is developed by extending the results from the time-dependent birth-death process. The implementation of such models in a full phylogenetic framework is expected to enable large scale probabilistic analysis of duplicates in comparative genomic studies. Conclusions: We develop an age-dependent birth-death model for understanding the mechanisms of gene retention, which allows a gene loss rate dependent on each duplication event. Simulation results indicate that different mechanisms of gene retentions produce distinct likelihood functions, which can be used with genomic data to quantitatively distinguish those mechanisms.
    • A genomic timescale for the origin of eukaryotes

      Hedges, SB; Chen, H; Kumar, S; Wang, DYC; Thompson, AS; Watanabe, H; Kumar, Sudhir|0000-0002-9918-8212 (2001-09-12)
      Background: Genomic sequence analyses have shown that horizontal gene transfer occurred during the origin of eukaryotes as a consequence of symbiosis. However, details of the timing and number of symbiotic events are unclear. A timescale for the early evolution of eukaryotes would help to better understand the relationship between these biological events and changes in Earth's environment, such as the rise in oxygen. We used refined methods of sequence alignment, site selection, and time estimation to address these questions with protein sequences from complete genomes of prokaryotes and eukaryotes. Results: Eukaryotes were found to evolve faster than prokaryotes, with those eukaryotes derived from eubacteria evolving faster than those derived from archaebacteria. We found an early time of divergence (∼4 billion years ago, Ga) for archaebacteria and the archaebacterial genes in eukaryotes. Our analyses support at least two horizontal gene transfer events in the origin of eukaryotes, at 2.7 Ga and 1.8 Ga. Time estimates for the origin of cyanobacteria (2.6 Ga) and the divergence of an early-branching eukaryote that lacks mitochondria (Giardia) (2.2 Ga) fall between those two events. Conclusions: We find support for two symbiotic events in the origin of eukaryotes: one premitochondrial and a later mitochondrial event. The appearance of cyanobacteria immediately prior to the earliest undisputed evidence for the presence of oxygen (2.4-2.2 Ga) suggests that the innovation of oxygenic photosynthesis had a relatively rapid impact on the environment as it set the stage for further evolution of the eukaryotic cell. © 2001 Hedges et al; licensee BioMed Central Ltd.
    • A genomic timescale of prokaryote evolution: Insights into the origin of methanogenesis, phototrophy, and the colonization of land

      Battistuzzi, FU; Feijao, A; Hedges, SB (2004-11-09)
      Background: The timescale of prokaryote evolution has been difficult to reconstruct because of a limited fossil record and complexities associated with molecular clocks and deep divergences. However, the relatively large number of genome sequences currently available has provided a better opportunity to control for potential biases such as horizontal gene transfer and rate differences among lineages. We assembled a data set of sequences from 32 proteins (∼7600 amino acids) common to 72 species and estimated phylogenetic relationships and divergence times with a local clock method. Results: Our phylogenetic results support most of the currently recognized higher-level groupings of prokaryotes. Of particular interest is a well-supported group of three major lineages of eubacteria (Actinobacteria, Deinococcus, and Cyanobacteria) that we call Terrabacteria and associate with an early colonization of land. Divergence time estimates for the major groups of eubacteria are between 2.5-3.2 billion years ago (Ga) while those for archaebacteria are mostly between 3.1-4.1 Ga. The time estimates suggest a Hadean origin of life (prior to 4.1 Ga), an early origin of methanogenesis (3.8-4.1 Ga), an origin of anaerobic methanotrophy after 3.1 Ga, an origin of phototrophy prior to 3.2 Ga, an early colonization of land 2.8-3.1 Ga, and an origin of aerobic methanotrophy 2.5-2.8 Ga. Conclusions: Our early time estimates for methanogenesis support the consideration of methane, in addition to carbon dioxide, as a greenhouse gas responsible for the early warming of the Earths' surface. Our divergence times for the origin of anaerobic methanotrophy are compatible with highly depleted carbon isotopic values found in rocks dated 2.8-2.6 Ga. An early origin of phototrophy is consistent with the earliest bacterial mats and structures identified as stromatolites, but a 2.6 Ga origin of cyanobacteria suggests that those Archean structures, if biologically produced, were made by anoxygenic photosynthesizers. The resistance to desiccation of Terrabacteria and their elaboration of photoprotective compounds suggests that the common ancestor of this group inhabited land. If true, then oxygenic photosynthesis may owe its origin to terrestrial adaptations. © 2004 Battistuzzi et al; licensee BioMed Central Ltd.
    • A graph convolutional network-based deep reinforcement learning approach for resource allocation in a cognitive radio network

      Zhao, D; Qin, H; Song, B; Han, B; Du, X; Guizani, M; Du, Xiaojiang|0000-0003-4235-9671 (2020-09-02)
      © 2020 by the authors. Licensee MDPI, Basel, Switzerland. Cognitive radio (CR) is a critical technique to solve the conflict between the explosive growth of traffic and severe spectrum scarcity. Reasonable radio resource allocation with CR can effectively achieve spectrum sharing and co-channel interference (CCI) mitigation. In this paper, we propose a joint channel selection and power adaptation scheme for the underlay cognitive radio network (CRN), maximizing the data rate of all secondary users (SUs) while guaranteeing the quality of service (QoS) of primary users (PUs). To exploit the underlying topology of CRNs, we model the communication network as dynamic graphs, and the random walk is used to imitate the users’ movements. Considering the lack of accurate channel state information (CSI), we use the user distance distribution contained in the graph to estimate CSI. Moreover, the graph convolutional network (GCN) is employed to extract the crucial interference features. Further, an end-to-end learning model is designed to implement the following resource allocation task to avoid the split with mismatched features and tasks. Finally, the deep reinforcement learning (DRL) framework is adopted for model learning, to explore the optimal resource allocation strategy. The simulation results verify the feasibility and convergence of the proposed scheme, and prove that its performance is significantly improved.
    • A guide to phylogenetic metrics for conservation, community ecology and macroecology

      Tucker, CM; Cadotte, MW; Carvalho, SB; Jonathan Davies, T; Ferrier, S; Fritz, SA; Grenyer, R; Helmus, MR; Jin, LS; Mooers, AO; Pavoine, S; Purschke, O; Redding, DW; Rosauer, DF; Winter, M; Mazel, F; Helmus, Matthew|0000-0003-3977-0507 (2017-05-01)
      © 2016 The Authors. The use of phylogenies in ecology is increasingly common and has broadened our understanding of biological diversity. Ecological sub-disciplines, particularly conservation, community ecology and macroecology, all recognize the value of evolutionary relationships but the resulting development of phylogenetic approaches has led to a proliferation of phylogenetic diversity metrics. The use of many metrics across the sub-disciplines hampers potential meta-analyses, syntheses, and generalizations of existing results. Further, there is no guide for selecting the appropriate metric for a given question, and different metrics are frequently used to address similar questions. To improve the choice, application, and interpretation of phylo-diversity metrics, we organize existing metrics by expanding on a unifying framework for phylogenetic information. Generally, questions about phylogenetic relationships within or between assemblages tend to ask three types of question: how much; how different; or how regular? We show that these questions reflect three dimensions of a phylogenetic tree: richness, divergence, and regularity. We classify 70 existing phylo-diversity metrics based on their mathematical form within these three dimensions and identify ‘anchor’ representatives: for α-diversity metrics these are PD (Faith’s phylogenetic diversity), MPD (mean pairwise distance), and VPD (variation of pairwise distances). By analysing mathematical formulae and using simulations, we use this framework to identify metrics that mix dimensions, and we provide a guide to choosing and using the most appropriate metrics. We show that metric choice requires connecting the research question with the correct dimension of the framework and that there are logical approaches to selecting and interpreting metrics. The guide outlined herein will help researchers navigate the current jungle of indices.
    • A guide to PIN1 function and mutations across cancers

      El Boustani, M; De Stefano, L; Caligiuri, I; Mouawad, N; Granchi, C; Canzonieri, V; Tuccinardi, T; Giordano, A; Rizzolio, F; Giordano, Antonio|0000-0002-5959-016X (2019-01-01)
      © 2019 El Boustani, De Stefano, Caligiuri, Mouawad, Granchi, Canzonieri, Tuccinardi, Giordano and Rizzolio. PIN1 is a member of a family of peptidylprolyl isomerases that bind phosphoproteins and catalyze the rapid cis–trans isomerization of proline peptidyl bonds, resulting in an alteration of protein structure, function, and stability. PIN1 is overexpressed in human cancers, suggesting it promotes tumorigenesis, but depending on the cellular context, it also acts as a tumor suppressor. Here, we review the role of PIN1 in cancer and the regulation of PIN1 expression, and catalog the single nucleotide polymorphisms, and mutations in PIN1 gene associated with cancer. In addition, we provide a 3D model of the protein to localize the mutated residues.
    • A heuristic information cluster search approach for precise functional brain mapping

      Asadi, N; Wang, Y; Olson, I; Obradovic, Z (2020-06-15)
      © 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc. Detection of the relevant brain regions for characterizing the distinction between cognitive conditions is one of the most sought after objectives in neuroimaging research. A popular approach for achieving this goal is the multivariate pattern analysis which is currently conducted through a number of approaches such as the popular searchlight procedure. This is due to several advantages such as being automatic and flexible with regards to size of the search region. However, these approaches suffer from a number of limitations which can lead to misidentification of truly informative regions which in turn results in imprecise information maps. These limitations mainly stem from several factors such as the fact that the information value of the search spheres are assigned to the voxel at the center of them (in case of searchlight), the requirement for manual tuning of parameters such as searchlight radius and shape, and high complexity and low interpretability in commonly used machine learning-based approaches. Other drawbacks include overlooking the structure and interactions within the regions, and the disadvantages of using certain regularization techniques in analysis of datasets with characteristics of common functional magnetic resonance imaging data. In this article, we propose a fully data-driven maximum relevance minimum redundancy search algorithm for detecting precise information value of the clusters within brain regions while alleviating the above-mentioned limitations. Moreover, in order to make the proposed method faster, we propose an efficient algorithmic implementation. We evaluate and compare the proposed algorithm with the searchlight procedure as well as least absolute shrinkage and selection operator regularization-based mapping approach using both real and synthetic datasets. The analysis results of the proposed approach demonstrate higher information detection precision and map specificity compared to the benchmark approaches.
    • A Hydrogel-Based Ultrasonic Backscattering Wireless Biochemical Sensing

      Nam, J; Byun, E; Shim, H; Kim, E; Islam, S; Park, M; Kim, A; Song, SH; Kim, Albert|0000-0003-1539-1246 (2020-11-27)
      © Copyright © 2020 Nam, Byun, Shim, Kim, Islam, Park, Kim and Song. Wireless monitoring of the physio-biochemical information is becoming increasingly important for healthcare. In this work, we present a proof-of-concept hydrogel-based wireless biochemical sensing scheme utilizing ultrasound. The sensing system utilizes silica-nanoparticle embedded hydrogel deposited on a thin glass substrate, which presents two prominent interfaces for ultrasonic backscattering (tissue/glass and hydrogel/glass). To overcome the effect of the varying acoustic properties of the intervening biological tissues between the sensor and the external transducer, we implemented a differential mode of ultrasonic back-scattering. Here, we demonstrate a wireless pH measurement with a resolution of 0.2 pH level change and a wireless sensing range around 10 cm in a water tank.
    • A hypothetical molecular mechanism for TRPV1 activation that invokes rotation of an S6 asparagine

      Kasimova, MA; Yazici, AT; Yudin, Y; Granata, D; Klein, ML; Rohacs, T; Carnevale, V; Carnevale, Vincenzo|0000-0002-0447-1278 (2018-11-01)
      © 2018 Kasimova et al. The transient receptor potential channel vanilloid type 1 (TRPV1) is activated by a variety of endogenous and exogenous stimuli and is involved in nociception and body temperature regulation. Although the structure of TRPV1 has been experimentally determined in both the closed and open states, very little is known about its activation mechanism. In particular, the conformational changes that occur in the pore domain and result in ionic conduction have not yet been identified. Here we suggest a hypothetical molecular mechanism for TRPV1 activation, which involves rotation of a conserved asparagine in S6 from a position facing the S4-S5 linker toward the pore. This rotation is associated with hydration of the pore and dehydration of the four peripheral cavities located between each S6 and S4-S5 linker. In light of our hypothesis, we perform bioinformatics analyses of TRP and other evolutionary related ion channels, evaluate newly available structures, and reexamine previously reported water accessibility and mutagenesis experiments. These analyses provide several independent lines of evidence to support our hypothesis. Finally, we show that our proposed molecular mechanism is compatible with the prevailing theory that the selectivity filter acts as a secondary gate in TRPV1.
    • A large-scale evaluation of computational protein function prediction

      Radivojac, P; Clark, WT; Oron, TR; Schnoes, AM; Wittkop, T; Sokolov, A; Graim, K; Funk, C; Verspoor, K; Ben-Hur, A; Pandey, G; Yunes, JM; Talwalkar, AS; Repo, S; Souza, ML; Piovesan, D; Casadio, R; Wang, Z; Cheng, J; Fang, H; Gough, J; Koskinen, P; Törönen, P; Nokso-Koivisto, J; Holm, L; Cozzetto, D; Buchan, DWA; Bryson, K; Jones, DT; Limaye, B; Inamdar, H; Datta, A; Manjari, SK; Joshi, R; Chitale, M; Kihara, D; Lisewski, AM; Erdin, S; Venner, E; Lichtarge, O; Rentzsch, R; Yang, H; Romero, AE; Bhat, P; Paccanaro, A; Hamp, T; Kaßner, R; Seemayer, S; Vicedo, E; Schaefer, C; Achten, D; Auer, F; Boehm, A; Braun, T; Hecht, M; Heron, M; Hönigschmid, P; Hopf, TA; Kaufmann, S; Kiening, M; Krompass, D; Landerer, C; Mahlich, Y; Roos, M; Björne, J; Salakoski, T; Wong, A; Shatkay, H; Gatzmann, F; Sommer, I; Wass, MN; Sternberg, MJE; Škunca, N; Supek, F; Bošnjak, M; Panov, P; Džeroski, S; Šmuc, T; Kourmpetis, YAI; Van Dijk, ADJ; Ter Braak, CJF; Zhou, Y; Gong, Q; Dong, X; Tian, W; Falda, M; Fontana, P; Lavezzo, E; Di Camillo, B; Toppo, S; Lan, L; Djuric, N; Guo, Y; Vucetic, S; Bairoch, A; Linial, M; Babbitt, PC; Brenner, SE; Orengo, C; Rost, B (2013-03-01)
      Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based critical assessment of protein function annotation (CAFA) experiment. Fifty-four methods representing the state of the art for protein function prediction were evaluated on a target set of 866 proteins from 11 organisms. Two findings stand out: (i) today's best protein function prediction algorithms substantially outperform widely used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is considerable need for improvement of currently available tools. © 2013 Nature America, Inc. All rights reserved.
    • A Letter to Mary Daly

      Levitt, Laura S. (2012)
    • A likelihood approach to estimate the number of co-infections

      Schneider, KA; Escalante, AA (2014-07-02)
      The number of co-infections of a pathogen (multiplicity of infection or MOI) is a relevant parameter in epidemiology as it relates to transmission intensity. Notably, such quantities can be built into a metric in the context of disease control and prevention. Having applications to malaria in mind, we develop here a maximum-likelihood (ML) framework to estimate the quantities of interest at low computational and no additional costs to study designs or data collection. We show how the ML estimate for the quantities of interest and corresponding confidence-regions are obtained from multiple genetic loci. Assuming specifically that infections are rare and independent events, the number of infections per host follows a conditional Poisson distribution. Under this assumption, we show that a unique ML estimate for the parameter (λ) describing MOI exists which is found by a simple recursion. Moreover, we provide explicit formulas for asymptotic confidence intervals, and show that profile-likelihood-based confidence intervals exist, which are found by a simple twodimensional recursion. Based on the confidence intervals we provide alternative statistical tests for the MOI parameter. Finally, we illustrate the methods on three malaria data sets. The statistical framework however is not limited to malaria. © 2014 Schneider, Escalante.