177,336 research outputs found
Deep Learning Enables Fast and Accurate Imputation of Gene Expression
No full textA question of fundamental biological significance is to what extent the expression of a subset of genes can be used to recover the full transcriptome, with important implications for biological discovery and clinical application. To address this challenge, we propose two novel deep learning methods, PMI and GAIN-GTEx, for gene expression imputation. In order to increase the applicability of our approach, we leverage data from GTEx v8, a reference resource that has generated a comprehensive collection of transcriptomes from a diverse set of human tissues. We show that our approaches compare favorably to several standard and state-of-the-art imputation methods in terms of predictive performance and runtime in two case studies and two imputation scenarios. In comparison conducted on the protein-coding genes, PMI attains the highest performance in inductive imputation whereas GAIN-GTEx outperforms the other methods in in-place imputation. Furthermore, our results indicate strong generalization on RNA-Seq data from 3 cancer types across varying levels of missingness. Our work can facilitate a cost-effective integration of large-scale RNA biorepositories into genomic studies of disease, with high applicability across diverse tissue types
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Graph representation forecasting of patient’s medical conditions: towards a digital twin
No full textObjective: Modern medicine needs to shift from a wait and react, curative
discipline to a preventative, interdisciplinary science aiming at providing
personalised, systemic and precise treatment plans to patients. The aim of this
work is to present how the integration of machine learning approaches with
mechanistic computational modelling could yield a reliable infrastructure to
run probabilistic simulations where the entire organism is considered as a
whole. Methods: We propose a general framework that composes advanced AI
approaches and integrates mathematical modelling in order to provide a
panoramic view over current and future physiological conditions. The proposed
architecture is based on a graph neural network (GNNs) forecasting clinically
relevant endpoints (such as blood pressure) and a generative adversarial
network (GANs) providing a proof of concept of transcriptomic integrability.
Results: We show the results of the investigation of pathological effects of
overexpression of ACE2 across different signalling pathways in multiple tissues
on cardiovascular functions. We provide a proof of concept of integrating a
large set of composable clinical models using molecular data to drive local and
global clinical parameters and derive future trajectories representing the
evolution of the physiological state of the patient. Significance: We argue
that the graph representation of a computational patient has potential to solve
important technological challenges in integrating multiscale computational
modelling with AI. We believe that this work represents a step forward towards
a healthcare digital twin
Synthesis, reactivity and structural studies of selenide bridged carboranyl compounds
No full textReaction of the lithium salt Li[1-R-1,2-closo-C2B10H10] with selenium under mild conditions, followed by hydrolysis gave the diselenide compound (1-Se-2-R-1,2-closo-C2B10H10)2 in contrast to the well-reported mercapto compounds 1-SH-2-R-1,2-closo-C2B10H10 obtained using a similar synthetic procedure. Details for the preparation and X-ray structural characterisation of the new compounds (2-Me-1,2-closo-C2B10H10)2Se (1), (1-Se-2-R-1,2-closo-C2B10H10)2 (R = Me,2, Ph, 3) are specified. To further explore the mechanism of the dimerization reaction, the complex [Au(1-Se-2-Me-1,2-closo- C2B10H10)(PPh3)] 4 was synthesized, confirming the existence of the intermediate Li[1-Se-2-R-1,2-closo-C2B10H10] at the early stages of the reaction before selenium oxidation. Theoretical calculations and cyclic voltammetry (CV) studies were carried out to compare the bonding nature of the sulfur and the selenium analog compounds. It was determined that diselenides have a higher tendency to reduce with respect to the disulfides and all chalcogen atoms were found to be positively charged
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Hypergraph factorization for multi-tissue gene expression imputation
No full textIntegrating gene expression across tissues and cell types is crucial for understanding the coordinated biological mechanisms that drive disease and characterize homoeostasis. However, traditional multi-tissue integration methods either cannot handle uncollected tissues or rely on genotype information, which is often unavailable and subject to privacy concerns. Here we present HYFA (hypergraph factorization), a parameter-efficient graph representation learning approach for joint imputation of multi-tissue and cell-type gene expression. HYFA is genotype agnostic, supports a variable number of collected tissues per individual, and imposes strong inductive biases to leverage the shared regulatory architecture of tissues and genes. In performance comparison on Genotype–Tissue Expression project data, HYFA achieves superior performance over existing methods, especially when multiple reference tissues are available. The HYFA-imputed dataset can be used to identify replicable regulatory genetic variations (expression quantitative trait loci), with substantial gains over the original incomplete dataset. HYFA can accelerate the effective and scalable integration of tissue and cell-type transcriptome biorepositories
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Letter from R. R. Zellick, Assistant Trust Officer, Anglo California National Bank of San Francisco, to Joseph R. Goodman, October 2, 1942
No full textLetter from R. R. Zellick, Assistant Trust Officer at The Anglo California National Bank of San Francisco, to Joseph R. Goodman, regarding property owned by Dave Tatsuno. Zellick mentions a dispute between current tenants and Tatsuno, and that Tatsuno has asked Goodman to help locate trustworthy tenants.Personal correspondence, organizational records, government documents, publications, and other papers created or collected by Joseph R. Goodman documenting the forced removal and incarceration of Japanese Americans during World War II, as well as organized resistance to incarceration. Included in the collection are records of the Japanese Young Men's Christian Association and the Japanese American Citizens' League in San Francisco, including papers of the Japanese YMCA's executive secretary Lincoln Kanai; Sakai family papers; Goodman's correspondence to and from Japanese American incarcerees, organizations opposing forced removal and incarceration of Japanese Americans, the War Relocation Authority, and others; publications, photographs, and ephemera from the Topaz Relocation Center, where Goodman taught high school; War Relocation Authority records and publications; and newspaper clippings, pamphlets, and reports about forced removal and incarceration created by various government, religious, and civic organizations, in California and nationwide
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Liftings for noncomplete probability spaces
No full textThe current state of knowledge concerning liftings for noncomplete probability spaces is discussed. This is a somewhat expanded version of the author's talk given at the 1991 Summer Conference on General Topology and Applications in Honor of Mary Ellen Rudin and Her Work.PT: S; CR: BURKE MR, IN PRESS P AM MATH S BURKE MR, 1991, ISRAEL J MATH, V73, P33 BURKE MR, 1992, ISRAEL J MATH, V79, P289 CARLSON T, THEOREM LIFTING CHRISTENSEN JPR, 1974, TOPOLOGY BOREL STRUC FREMLIN DH, 1989, HDB BOOLEAN ALGEBRAS, P877 INOESCUTULCEA A, 1966, 5TH P BERK S MATH ST, V2 IONESCUTULCEA A, 1967, CONTRIBUTIONS PROB 1, P63 IONESCUTULCEA A, 1969, TOPICS THEORY LIFTIN JECH TJ, 1978, SET THEORY JOHNSON RA, 1980, P AM MATH SOC, V80, P234 JUST W, IN PRESS T AM MATH S KUPKA J, 1983, INDIANA U MATH J, V32, P717 LOSERT V, 1983, LNM, V1080, P95 MAHARAM D, 1958, P AM MATH SOC, V9, P987 SHELAH S, 1983, ISRAEL J MATH, V45, P90 TALAGRAND M, 1982, P AM MATH SOC, V84, P379 VONNEUMANN J, 1931, CRELLES J MATH, V165, P109; NR: 18; TC: 0; J9: ANN N Y ACAD SCI; PG: 4; GA: BZ86BSource type: Electronic(1
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