Статті в журналах: "Text genetics"

1

HUDSON, RICHARD R. "Population genetics text." Journal of Heredity 77, no. 2 (March 1986): 141–42. http://dx.doi.org/10.1093/oxfordjournals.jhered.a110199.

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2

Morrison, Patrick J. "A classic genetic text about classic genetic texts." European Journal of Human Genetics 13, no. 7 (June 23, 2005): 892. http://dx.doi.org/10.1038/sj.ejhg.5201417.

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3

Gibson, Greg, and David B. Goldstein. "Human Genetics: The Hidden Text of Genome-wide Associations." Current Biology 17, no. 21 (November 2007): R929—R932. http://dx.doi.org/10.1016/j.cub.2007.08.044.

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4

Cameron, Vicki L. "Teaching Advanced Genetics Without Lectures." Genetics 165, no. 3 (November 1, 2003): 945–50. http://dx.doi.org/10.1093/genetics/165.3.945.

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Abstract In an effort to increase student engagement and therefore student learning, an advanced genetics course was developed in which traditional lectures were eliminated. Instead, students were required to complete reading assignments before each class meeting, and those readings were then the topic of group discussion. Assigned readings alternated between text assignments and articles from the primary literature. Students were made accountable for their own preparation by the administration of a quiz at the start of each class. Group discussion of the topics engaged students in the learning process and readministration of the quiz at the end of class allowed them to benefit from the group interaction and understanding. Interspersing text readings and primary literature led to student understanding of how genetic knowledge is acquired and interpreted and how experimental detail leads to the construction of general models.

5

Vazquez, M., P. Carmona-Saez, R. Nogales-Cadenas, M. Chagoyen, F. Tirado, J. M. Carazo, and A. Pascual-Montano. "SENT: semantic features in text." Nucleic Acids Research 37, Web Server (May 20, 2009): W153—W159. http://dx.doi.org/10.1093/nar/gkp392.

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6

Hooper, Stephen R. "The Genetics of Neurobehavioral Manifestation: Linkages and Prospects." Journal of the International Neuropsychological Society 8, no. 1 (January 2002): 140–41. http://dx.doi.org/10.1017/s1355617702251140.

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While genetic linkages to a variety of disorders have been suspected for decades, it has only been relatively recently that these linkages have come to be understood to a greater degree. The search for the genetic basis of some neurodevelopmental disorders, such as learning disabilities, has been elusive and fraught with complex hurdles, the genetic basis of other neurodevelopmental disorders, such as Down syndrome, has been much more clear. Other childhood disorders, such as Turner syndrome and fragile X syndrome, also documented clearly defined genotypes. Even when a clear genetic contribution is known (i.e., the genotype), the exact neurobehavioral manifestations (i.e., the phenotypes) remain unclear or poorly documented for many disorders. This edited volume addresses this quest and, perhaps, provides one of the most comprehensive descriptions of the available literature in the interface between genetics and behavior in childhood. As noted by the editors, one of the major objectives of this text is to provide students, clinicians, and researchers with a working knowledge base of behavioral genetics. In this regard, the editors wanted to provide a comprehensive text that was “organized in a framework that is understandable and immediately useful in clinical practice” (p. 6).

7

Armstrong, Graeme. "Conservation and the Genetics of Populations." Pacific Conservation Biology 14, no. 2 (2008): 146. http://dx.doi.org/10.1071/pc080146.

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I am sure many readers have experienced the excruciating situation of being involved in a conservation project that makes no effort to include a genetic component in the methodology. This is often due to a lack of understanding by managers compounded by an inability of biologists to remedy this situation by demonstrating the importance of genetics to the desired conservation outcome. The authors of Conservation and the Genetics of Populations have aimed their text at ?broadly trained biologists? to enable an understanding and application of genetic principles to conservation problems. If successful this would go a long way to alleviating this problem.

8

Islamaj, Rezarta, Dongseop Kwon, Sun Kim, and Zhiyong Lu. "TeamTat: a collaborative text annotation tool." Nucleic Acids Research 48, W1 (May 8, 2020): W5—W11. http://dx.doi.org/10.1093/nar/gkaa333.

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Abstract Manually annotated data is key to developing text-mining and information-extraction algorithms. However, human annotation requires considerable time, effort and expertise. Given the rapid growth of biomedical literature, it is paramount to build tools that facilitate speed and maintain expert quality. While existing text annotation tools may provide user-friendly interfaces to domain experts, limited support is available for figure display, project management, and multi-user team annotation. In response, we developed TeamTat (https://www.teamtat.org), a web-based annotation tool (local setup available), equipped to manage team annotation projects engagingly and efficiently. TeamTat is a novel tool for managing multi-user, multi-label document annotation, reflecting the entire production life cycle. Project managers can specify annotation schema for entities and relations and select annotator(s) and distribute documents anonymously to prevent bias. Document input format can be plain text, PDF or BioC (uploaded locally or automatically retrieved from PubMed/PMC), and output format is BioC with inline annotations. TeamTat displays figures from the full text for the annotator's convenience. Multiple users can work on the same document independently in their workspaces, and the team manager can track task completion. TeamTat provides corpus quality assessment via inter-annotator agreement statistics, and a user-friendly interface convenient for annotation review and inter-annotator disagreement resolution to improve corpus quality.

9

Ravine, D. "Molecular Medicine. An Introductory Text for Students." Journal of Medical Genetics 32, no. 2 (February 1, 1995): 160. http://dx.doi.org/10.1136/jmg.32.2.160.

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10

Zeng, Z. B., and C. C. Cockerham. "Variance of neutral genetic variances within and between populations for a quantitative character." Genetics 129, no. 2 (October 1, 1991): 535–53. http://dx.doi.org/10.1093/genetics/129.2.535.

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Abstract The variances of genetic variances within and between finite populations were systematically studied using a general multiple allele model with mutation in terms of identity by descent measures. We partitioned the genetic variances into components corresponding to genetic variances and covariances within and between loci. We also analyzed the sampling variance. Both transient and equilibrium results were derived exactly and the results can be used in diverse applications. For the genetic variance within populations, sigma 2 omega, the coefficient of variation can be very well approximated as [formula: see text] for a normal distribution of allelic effects, ignoring recurrent mutation in the absence of linkage, where m is the number of loci, N is the effective population size, theta 1(0) is the initial identity by descent measure of two genes within populations and t is the generation number. The first term is due to genic variance, the second due to linkage disequilibrium, and third due to sampling. In the short term, the variation is predominantly due to linkage disequilibrium and sampling; but in the long term it can be largely due to genic variance. At equilibrium with mutation [formula: see text] where u is the mutation rate. The genetic variance between populations is a parameter. Variance arises only among sample estimates due to finite sampling of populations and individuals. The coefficient of variation for sample gentic variance between populations, sigma 2b, can be generally approximated as [formula: see text] when the number of loci is large where S is the number of sampling populations.

11

Van Vooren, Steven W., Joke Allemeersch, Wouter Van Delm, Bart De Moor, Joris R. Vermeesch, and Yves Moreau. "O12: Text Mining for Constitutional Cytogenetics." European Journal of Medical Genetics 48, no. 4 (October 2005): 468–69. http://dx.doi.org/10.1016/j.ejmg.2005.10.037.

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12

Matiiuk, V. V., and T. V. Kushnirova. "Features of translation of scientific terms in the genetic field into Ukrainian." Bulletin of Luhansk Taras Shevchenko National University, no. 2 (350) (2022): 112–19. http://dx.doi.org/10.12958/2227-2844-2022-2(350)-112-119.

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The article considers scientific terms and methods of their translation on the example of a number of articles in the field of genetics. The experience and practical work of leading specialists in the field of genetics and translation are analyzed. The aim of the work was a thorough analysis of the translation of scientific terms on genetic topics. Currently, there is a problem of unification of selection and genetic terminology, which is actively developing today. The term becomes the core of the genetic text, because it is from understanding a certain concept, you can come to understand the full test. Usually the genetic text is characterized by one and multi-component vocabulary, in particular 1, 2, 3 component terms, which are translated by transliteration, transcription and tracing; sometimes all these methods are combined to form a corresponding concept. The article analyzes the translation of proper names of genetic topics. In most cases in genetics, when translating proper names into another language, translators use the method of transliteration, sometimes using tracing. In this case, the proper names of the source language are transmitted in the letters of the Ukrainian alphabet without considering the peculiarities of pronunciation. There are cases when the dictionary does not have an exact correspondence to a certain term, or the use of these methods is illogical, then translators resort to other translation transformations, especially when the terminology is new. The paper notes that conditionally all texts can be divided into two groups: texts with already known concepts and texts that introduce new concepts, which are usually expressed in new terms. The article notes that a promising task of modern researchers is to create bilingual dictionaries and reference books in the genetic field, which will unify the terminological apparatus of a particular field.

13

Rodriguez-Esteban, R., P. M. Roberts, and M. E. Crawford. "Identifying and classifying biomedical perturbations in text." Nucleic Acids Research 37, no. 3 (December 12, 2008): 771–77. http://dx.doi.org/10.1093/nar/gkn986.

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14

Harris, Rodney. "Molecular medicine: An introductory text for students." Trends in Genetics 10, no. 7 (July 1994): 259. http://dx.doi.org/10.1016/0168-9525(94)90175-9.

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15

Subbulakshmi, S. "Thiruvāsagam – A Text of Multi-Discipline." Shanlax International Journal of Arts, Science and Humanities 9, no. 4 (April 1, 2022): 50–57. http://dx.doi.org/10.34293/sijash.v9i4.4813.

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Thiruvāsagam authored by Saint Mānikkavāsagar establishes the Author’s diverse personality and his expertise in multiple areas like Physics, Astronomy, Philosophy, Literature, Scripture, Science, Medicine, Defence, Genetics, Law, History, Geography, Human psychology, Politics, Fine arts, and so on. Thiruvāsagam proves the author is a Master of all Trades, a Multi faceted personality. Thiruvāsagam is a multi branched, multifarious text though it belongs to divine and Bakthi literature.

16

Komatsudaa, T., Y. Manoa, Y. Turuspekovb, I. Hondab, N. Kawadab, and Y. Watanabe. "Inheritance and genetic diversity of flowering types in barley." Czech Journal of Genetics and Plant Breeding 41, Special Issue (July 31, 2012): 194. http://dx.doi.org/10.17221/6167-cjgpb.

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17

YANG, XIAOLI, YIFAN CAI, and CHARLES TSENG. "AN INTERACTIVE COMPUTER FRAMEWORK FOR LEARNING GENETICS." International Journal of Information Acquisition 09, no. 03n04 (September 2013): 1350019. http://dx.doi.org/10.1142/s0219878913500198.

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To enhance the effectiveness of learning genetics, we have developed a series of individual computer programs integrating interactivity with animated processes. It was noted that, although the content of the programs varied, the programs all contained a number of common features, including the ability to display text and images, present animated content, and interact with the user. These common features led us to the development of an innovative and unified framework of integrated functions for modeling and simulations. The framework, named "GeneAct" was developed to standardize and accelerate the development of the computer based genetics learning programs and was used as the application programming interface (API). The API allows the content to be imbued with rich text (text with multi-formats), static images, and animations; and it also allows the program to be interactive.

18

Sharma, I., N. S. Bains, B. Raj, A. Sirari та R. C. Sharma. "Genetics of Karnal bunt resistance: use of Tilletia indica populations at diﬀerent levels of heterogeneity". Czech Journal of Genetics and Plant Breeding 42, Special Issue (1 серпня 2012): 26–31. http://dx.doi.org/10.17221/6226-cjgpb.

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19

Fenoglio, Irène. "Textual Genetics and Manuscript in Word Processing. A new Definition of the Text?" New Approaches in Text Linguistics 23 (September 25, 2009): 45–61. http://dx.doi.org/10.1075/bjl.23.05fen.

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Abstract: Very little research has been devoted to the way in which the textual genetics approaches the manuscripts in the text processing. However the future of the genetics depends, partly, on the interest which one can carry to this new materiality of the manuscript. The notion of text, the concept of what text is, have they been changed, or at least modified by the use of text processing? To write a text is to elaborate a discourse in the form of an utterance and to record it. The order of the discourse, in other words, the semiotic (the linguistic recognizable) / semantic (the meaning expressed (uttered) in the discourse) ratio should in no way be modified by the use of text processing. What changes, on the other hand, it is the materialization of the paper support of the text and consequently the status of this materialization.

20

Goncharov, N. P. "Comparative-genetic analysis – a base for wheat taxonomy revision." Czech Journal of Genetics and Plant Breeding 41, Special Issue (July 31, 2012): 52–55. http://dx.doi.org/10.17221/6132-cjgpb.

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21

Weldon, Christine B., Su-Ying Liang, Kathryn A. Phillips, Michael P. Douglas, Maren Theresa Scheuner, Allison W. Kurian, Kendra Schaa, Breanna Roscow, Deanna Erwin, and Julia Rachel Trosman. "Multicancer hereditary syndrome testing: Genetic counselors’ perspectives." Journal of Clinical Oncology 39, no. 15_suppl (May 20, 2021): 10594. http://dx.doi.org/10.1200/jco.2021.39.15_suppl.10594.

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10594 Background: The accessibility of cancer hereditary syndrome testing has increased, and the cost has declined significantly in the past few years. We conducted a national, quantitative survey of genetic counselors (GCs) to assess their perspectives on what influences hereditary cancer genetic testing decisions and practices, with a focus on cost. This survey was funded by NIH, conducted by UCSF TRANSPERS, and supported by the National Society of Genetic Counselors (NSGC). Methods: The survey was developed through literature review, expert interviews, and a pilot. Sent to the NSGC Cancer Special Interest Group via email. Chi-square tests were used to examine variability. Results: The survey response rate was 56% (202/363). Multiple hereditary cancer syndrome tests are discussed often/always by 86% of genetic counselors (GCs). The existence of an institutional protocol on multiple hereditary cancer syndrome testing was reported by 35.4% of GCs. When asked about GC counseling encounters, GCs report insurance rarely/never pays for: 25.2% pre-test in-person, 39.7% for pre-test tele-genetics, 35.4% post-test in-person, and 52.9% post-test tele-genetics. GCs rated clinical factors higher than cost as influencing decision for multiple hereditary syndrome cancer testing (table); the total cost of the test was least important. These patterns were similar across the GCs institution types and years in practice. Conclusions: We found consistent use of multiple hereditary cancer syndrome tests, with less focus on cost, out-of-pocket, and insurance coverage and more of a focus on clinical indicators. GCs reported challenges with reimbursement for GC counseling encounters. The shift toward more genetic counseling encounters via tele-genetics necessitates evaluation of insurance reimbursement.[Table: see text]

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Weldon, Christine B., Su-Ying Liang, Kathryn A. Phillips, Michael P. Douglas, Maren Theresa Scheuner, Allison W. Kurian, Kendra Schaa, Breanna Roscow, Deanna Erwin, and Julia R. Trosman. "Multicancer hereditary syndrome testing: Genetic counselors’ perspectives." Journal of Clinical Oncology 39, no. 28_suppl (October 1, 2021): 106. http://dx.doi.org/10.1200/jco.2020.39.28_suppl.106.

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106 Background: The accessibility of cancer hereditary syndrome testing has increased, and the cost has declined significantly in the past few years. We conducted a national, quantitative survey of genetic counselors (GCs) to assess their perspectives on what influences hereditary cancer genetic testing decisions and practices, with a focus on cost. This survey was funded by NIH, conducted by UCSF TRANSPERS, and supported by the National Society of Genetic Counselors(NSGC). Methods: The survey was developed through literature review, expert interviews, and a pilot. Sent to the NSGC Cancer Special Interest Group via email. Chi-square tests were used to examine variability. Results: The survey response rate was 56% (202/363). Multiple hereditary cancer syndrome tests are discussed often/always by 86% of genetic counselors (GCs).The existence of an institutional protocol on multiple hereditary cancer syndrome testing was reported by 35.4% of GCs. When asked about GC counseling encounters, GCs report insurance rarely/never pays for: 25.2% pre-test in-person,39.7% for pre-test tele-genetics, 35.4% post-test in-person, and 52.9% post-test tele-genetics. GCs rated clinical factors higher than cost as influencing decision for multiple hereditary syndrome cancer testing (table); the total cost of the test was least important. These patterns were similar across the GCs institution types and years in practice. Conclusions: We found consistent use of multiple hereditary cancer syndrome tests, with less focus on cost, out-of-pocket, and insurance coverage and more of a focus on clinical indicators. GCs reported challenges with reimbursement for GC counseling encounters. The shift toward more genetic counseling encounters via tele-genetics necessitates evaluation of insurance reimbursement.[Table: see text]

23

Song, Min, Seung Han Baek, Go Eun Heo, and Jeong-Hoon Lee. "Inferring Drug-Protein–Side Effect Relationships from Biomedical Text." Genes 10, no. 2 (February 19, 2019): 159. http://dx.doi.org/10.3390/genes10020159.

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Background: Although there are many studies of drugs and their side effects, the underlying mechanisms of these side effects are not well understood. It is also difficult to understand the specific pathways between drugs and side effects. Objective: The present study seeks to construct putative paths between drugs and their side effects by applying text-mining techniques to free text of biomedical studies, and to develop ranking metrics that could identify the most-likely paths. Materials and Methods: We extracted three types of relationships—drug-protein, protein-protein, and protein–side effect—from biomedical texts by using text mining and predefined relation-extraction rules. Based on the extracted relationships, we constructed whole drug-protein–side effect paths. For each path, we calculated its ranking score by a new ranking function that combines corpus- and ontology-based semantic similarity as well as co-occurrence frequency. Results: We extracted 13 plausible biomedical paths connecting drugs and their side effects from cancer-related abstracts in the PubMed database. The top 20 paths were examined, and the proposed ranking function outperformed the other methods tested, including co-occurrence, COALS, and UMLS by P@5-P@20. In addition, we confirmed that the paths are novel hypotheses that are worth investigating further. Discussion: The risk of side effects has been an important issue for the US Food and Drug Administration (FDA). However, the causes and mechanisms of such side effects have not been fully elucidated. This study extends previous research on understanding drug side effects by using various techniques such as Named Entity Recognition (NER), Relation Extraction (RE), and semantic similarity. Conclusion: It is not easy to reveal the biomedical mechanisms of side effects due to a huge number of possible paths. However, we automatically generated predictable paths using the proposed approach, which could provide meaningful information to biomedical researchers to generate plausible hypotheses for the understanding of such mechanisms.

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Kolchinsky, Artemy, Alaa Abi-Haidar, Jasleen Kaur, Ahmed Abdeen Hamed, and Luis M. Rocha. "Classification of Protein-Protein Interaction Full-Text Documents Using Text and Citation Network Features." IEEE/ACM Transactions on Computational Biology and Bioinformatics 7, no. 3 (July 2010): 400–411. http://dx.doi.org/10.1109/tcbb.2010.55.

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BASYSTIUK, Oleh, and Nataliia MELNYKOVA. "MULTIMODAL SPEECH RECOGNITION BASED ON AUDIO AND TEXT DATA." Herald of Khmelnytskyi National University. Technical sciences 313, no. 5 (October 27, 2022): 22–25. http://dx.doi.org/10.31891/2307-5732-2022-313-5-22-25.

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Systems of machine translation of texts from one language to another simulate the work of a human translator. Their performance depends on the ability to understand the grammar rules of the language. In translation, the basic units are not individual words, but word combinations or phraseological units that express different concepts. Only by using them, more complex ideas can be expressed through the translated text. The main feature of machine translation is different length for input and output. The ability to work with different lengths of input and output provides us with the approach of recurrent neural networks. A recurrent neural network (RNN) is a class of artificial neural network that has connections between nodes. In this case, a connection refers to a connection from a more distant node to a less distant node. The presence of connections allows the RNN to remember and reproduce the entire sequence of reactions to one stimulus. From the point of view of programming, such networks are analogous to cyclic execution, and from the point of view of the system, such networks are equivalent to a state machine. RNNs are commonly used to process word sequences in natural language processing. Usually, a hidden Markov model (HMM) and an N-program language model are used to process a sequence of words. Deep learning has completely changed the approach to machine translation. Researchers in the deep learning field has created simple solutions based on machine learning that outperform the best expert systems. In this paper was reviewed the main features of machine translation based on recurrent neural networks. The advantages of systems based on RNN using the sequence-to-sequence model against statistical translation systems are also highlighted in the article. Two machine translation systems based on the sequence-to-sequence model were constructed using Keras and PyTorch machine learning libraries. Based on the obtained results, libraries analysis was done, and their performance comparison.

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Zolyan, Suren T., and Renad I. Zhdanov. "Genome as (hyper)text: From metaphor to theory." Semiotica 2018, no. 225 (November 6, 2018): 1–18. http://dx.doi.org/10.1515/sem-2016-0214.

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Abstract The similarity between language and genetic information transmission processing has been recognized since molecular genetics was founded. Numerous attempts have been made to use linguistics techniques to decipher protein genes. The modest informational impact of various approaches to decoding the “protein language” was predictable: this type of technique is limited by the processes of encoding and at best helps compile a dictionary of units. However, this technique cannot describe a language and identify the semantic and textual structures that are decisive for communication. Thus, the functions of a large amount of non-coding DNA remain unclear. A text (but not a sign) should be regarded as an artefact of the creation, transmission, conservation and transformation of information. A general theory of text should be capable of describing linguistic texts and the process of their structuring, functioning and transformation. It should also be able to represent the biochemical structure of a genome as a hypertext that consists of an ordered subset of other texts. A text can be considered to be a quasi-organism that possesses memory, creative-cognitive characteristics and communicative force, and a cell can be considered as a quasi-intelligence capable of manipulating abstract semiotic entities. Such an approach requires the construction of a new, multimodal, and text-oriented version of semiotics (next-generation semiotics), in which text and context are the basic concepts and signs and meanings are considered to be context-dependent variables and, simultaneously, context-forming operators.

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Nowling, Ronald J., and Scott J. Emrich. "Adjusted likelihood-ratio test for variants with unknown genotypes." Journal of Bioinformatics and Computational Biology 16, no. 05 (October 2018): 1840020. http://dx.doi.org/10.1142/s0219720018400206.

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Association tests performed with the Likelihood-Ratio Test (LR Test) can be an alternative to [Formula: see text], which is often used in population genetics to find variants of interest. Because the LR Test has several properties that could make it preferable to [Formula: see text], we propose a novel approach for modeling unknown genotypes in highly-similar species. To show the effectiveness of this LR Test approach, we apply it to single-nucleotide polymorphisms (SNPs) associated with the recent speciation of the malaria vectors Anopheles gambiae and Anopheles coluzzii and compare to [Formula: see text].

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Titis Hutama Syah. "The Role of Genetics in Domestic Research on Forestry Issues: A Text Mining Analysis." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 6, no. 6 (December 29, 2022): 1006–13. http://dx.doi.org/10.29207/resti.v6i6.4228.

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As a megadiverse country, Indonesia has plentiful genetic resources. The interest of domestic researchers in it and its relation to forestry scope is the focus of this paper. The objective is to determine the genetics aspects represented in forestry scholarly articles. Text mining analysis is carried out for the abstract articles, followed by topic modeling and trend analysis. Python libraries were used to conduct this research. Garuda website was the main source of the data collection. Natural language Toolkits (NLTK) were used to retrieve article information from Garuda. Sci-kit learn (SKLearn) of Latent Dirichlet Allocation module was used for topic modeling analysis, and pyLDAVis was used to represent it. SKLearn was also used for trending analysis. After article text retrieval, three topic clusters were found: forest diversity, products, and land use. The topics were scattered in 1966 abstract articles that were found during data retrieval. Article growth showed the quadratic pattern known after regression analysis. The trend showed the rapid growth of topics and scholars' interest, but the number of articles was low compared to the total articles on the Garuda portal.

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Wei, Chih-Hsuan, Alexis Allot, Robert Leaman, and Zhiyong Lu. "PubTator central: automated concept annotation for biomedical full text articles." Nucleic Acids Research 47, W1 (May 22, 2019): W587—W593. http://dx.doi.org/10.1093/nar/gkz389.

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AbstractPubTator Central (https://www.ncbi.nlm.nih.gov/research/pubtator/) is a web service for viewing and retrieving bioconcept annotations in full text biomedical articles. PubTator Central (PTC) provides automated annotations from state-of-the-art text mining systems for genes/proteins, genetic variants, diseases, chemicals, species and cell lines, all available for immediate download. PTC annotates PubMed (29 million abstracts) and the PMC Text Mining subset (3 million full text articles). The new PTC web interface allows users to build full text document collections and visualize concept annotations in each document. Annotations are downloadable in multiple formats (XML, JSON and tab delimited) via the online interface, a RESTful web service and bulk FTP. Improved concept identification systems and a new disambiguation module based on deep learning increase annotation accuracy, and the new server-side architecture is significantly faster. PTC is synchronized with PubMed and PubMed Central, with new articles added daily. The original PubTator service has served annotated abstracts for ∼300 million requests, enabling third-party research in use cases such as biocuration support, gene prioritization, genetic disease analysis, and literature-based knowledge discovery. We demonstrate the full text results in PTC significantly increase biomedical concept coverage and anticipate this expansion will both enhance existing downstream applications and enable new use cases.

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Antoniuk, Mateusz. "This page will cry here for centuries… Słowacki, Yeats and the (Im)Materiality of the Text." Textual Cultures 10, no. 1 (December 20, 2016): 37–55. http://dx.doi.org/10.14434/tc.v10i1.13335.

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This essay concerns the famous Polish Romantic poem written by Juliusz Słowacki. The close reading of the text leads me toward the genetics analysis of it’s first draft (which appears to be at once “lost” and “regained”) as well as evokes the meditation about the Słowacki’s philosophy of textual representation (which appears to be deeply ambiguous). My article is inspired by George Bornstein conception of textual materiality and by genetic criticism methodology. I also demonstrate the parallel between poem of Słowacki and lyric When You Are Old, written by W.B. Yeats.

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Calhoun, Jeffrey Dennis, and Gemma L. Carvill. "Epilepsy Genetics: What Once Was Rare, Is Now Common." Epilepsy Currents 20, no. 4 (June 19, 2020): 221–23. http://dx.doi.org/10.1177/1535759720933232.

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32

Lee, Hodong, Gwan-Su Yi, and Jong C. Park. "E3Miner: a text mining tool for ubiquitin-protein ligases." Nucleic Acids Research 36, suppl_2 (May 15, 2008): W416—W422. http://dx.doi.org/10.1093/nar/gkn286.

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Bunnell, Ann, Kate Principe, Gayle Patel, Trisha Nichols, Sara Mokhtary, John F. Sandbach, and Vanessa Torres. "Genetic evaluations and testing rates for hereditary breast and ovarian cancer syndrome in a community oncology setting." Journal of Clinical Oncology 41, no. 16_suppl (June 1, 2023): e22533-e22533. http://dx.doi.org/10.1200/jco.2023.41.16_suppl.e22533.

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e22533 Background: Several professional medical societies recommend genetic evaluations and testing for individuals with a personal and/or family cancer history. The National Comprehensive Cancer Network (NCCN) outlines germline testing criteria for breast, ovarian, and pancreatic cancer predisposition genes. This study aims to assess the genetic evaluation and testing rates in community oncology centers among patients who qualify based on their personal history of cancer. Methods: A retrospective study assessed patients diagnosed at any Texas Oncology site between 1/01/2017 and 12/31/2019. Using NCCN Genetic/Familial High-Risk Assessment: Breast, Ovarian, and Pancreatic V1.2020, individuals with the following cancer diagnoses were included: epithelial ovarian, breast < 45 years, triple negative breast < 60 years, metastatic HER2 negative breast, male breast, exocrine pancreatic, or metastatic prostate. Data was obtained from electronic medical records. The project was approved by the Texas Oncology Privacy Board. Results: Of the 10,202 patients included, 6033 (59%) underwent genetic testing. Only 3660 (36%) had a genetic evaluation, and of those, 2720 (74%) were conducted within Texas Oncology. Younger patients were significantly more likely to be tested than those diagnosed at older ages (p = 2.2e-16). Testing rates were significantly higher (p = 8.95e-07) at sites that employ a provider with genetics training; moreover, the rates of evaluation and testing trended upward, the longer those providers had been offering genetics services. Of the patients without test results, most (76%) had neither a genetics referral nor germline test order documented, suggesting an opportunity for provider education. Conclusions: Most patients who met criteria underwent genetic testing, but the rates varied by cancer type. Patients with breast cancer were most likely to have genetic testing. This study proved that having a genetics provider on staff significantly improved testing rates for patients who qualify. However, given that 100% of the cohort qualified and only 59% underwent testing, quality improvement measures are needed to increase the rate of genetic evaluations and testing for these diagnoses. [Table: see text]

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Solinas, Pier Giorgio. "Genealogy, kinship, genetics: Maintaining distances?" Anuac 2, no. 2 (June 28, 2015): 1–25. http://dx.doi.org/10.7340/anuac2239-625x-99.

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Drawing on examples from Indian ethnography and not only, this paper seeks to identify, ranging from research and representations of geneticists and local images, to systematize the idea of descent on three different levels: the first about the field of relationships between people and groups, families, genealogies; the second about the terms and kinship relations, ie the raw material of visible genealogies; the third about the genetic text and the classes that it generates.

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Wei, Chih-Hsuan, Hung-Yu Kao, and Zhiyong Lu. "PubTator: a web-based text mining tool for assisting biocuration." Nucleic Acids Research 41, W1 (May 22, 2013): W518—W522. http://dx.doi.org/10.1093/nar/gkt441.

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McEntyre, J. R., S. Ananiadou, S. Andrews, W. J. Black, R. Boulderstone, P. Buttery, D. Chaplin, et al. "UKPMC: a full text article resource for the life sciences." Nucleic Acids Research 39, Database (November 9, 2010): D58—D65. http://dx.doi.org/10.1093/nar/gkq1063.

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Lachmann, Alexander, Brian M. Schilder, Megan L. Wojciechowicz, Denis Torre, Maxim V. Kuleshov, Alexandra B. Keenan, and Avi Ma’ayan. "Geneshot: search engine for ranking genes from arbitrary text queries." Nucleic Acids Research 47, W1 (May 22, 2019): W571—W577. http://dx.doi.org/10.1093/nar/gkz393.

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Abstract The frequency by which genes are studied correlates with the prior knowledge accumulated about them. This leads to an imbalance in research attention where some genes are highly investigated while others are ignored. Geneshot is a search engine developed to illuminate this gap and to promote attention to the under-studied genome. Through a simple web interface, Geneshot enables researchers to enter arbitrary search terms, to receive ranked lists of genes relevant to the search terms. Returned ranked gene lists contain genes that were previously published in association with the search terms, as well as genes predicted to be associated with the terms based on data integration from multiple sources. The search results are presented with interactive visualizations. To predict gene function, Geneshot utilizes gene–gene similarity matrices from processed RNA-seq data, or from gene–gene co-occurrence data obtained from multiple sources. In addition, Geneshot can be used to analyze the novelty of gene sets and augment gene sets with additional relevant genes. The Geneshot web-server and API are freely and openly available from https://amp.pharm.mssm.edu/geneshot.

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Baum, B. R. "Inferring genetic relationship among haplomes in Triticeae: The utility of the 5S DNA units with examples." Czech Journal of Genetics and Plant Breeding 41, Special Issue (July 31, 2012): 39–51. http://dx.doi.org/10.17221/6131-cjgpb.

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Sun, Zhaohui, Mounir Errami, Tara Long, Chris Renard, Nishant Choradia, and Harold Garner. "Systematic Characterizations of Text Similarity in Full Text Biomedical Publications." PLoS ONE 5, no. 9 (September 15, 2010): e12704. http://dx.doi.org/10.1371/journal.pone.0012704.

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Savinova, A. V., N. A. Shnayder, and R. F. Nasyrova. "Genetics of familial amyotrophic lateral sclerosis." Bulletin of Siberian Medicine 20, no. 3 (October 22, 2021): 193–202. http://dx.doi.org/10.20538/1682-0363-2021-3-193-202.

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To analyze results of the studies covering modern scientific views on the genetics of familial amyotrophic lateral sclerosis (FALS).We searched for full-text publications containing the key words “amyotrophic lateral sclerosis”, “FALS”, and “genetics” in the literature for the past 10 years in both Russian and English in eLibrary, PubMed, Web of Science, and OMIM databases. In addition, the review includes earlier publications of historical interest.This review summarizes all existing information on four most widespread genes associated with FALS: SOD1, TARDBP, FUS, and C9ORF72. The review also describes the functions of these genes and possible pathogenetic mechanisms of motor neuron death in amyotrophic lateral sclerosis (ALS), such as mitochondrial dysfunction, oxidative stress, glutamate excitotoxicity, damage to axonal transport components, and pathological neurofilament aggregation.As modern methods of molecular genetic diagnostics evolve, our knowledge about multifactorial FALS genetics expands. This information should be taken into consideration in clinical practice of neurologists. Information about the genes associated with ALS and understanding of particular pathogenetic mechanisms of the disease play a key role in the development of effective therapeutic strategies.

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Fenton, Mary Anne, Tara Szyamnski, Kimberly Perez, Cindy Benson, and Chanika Phornphutkul. "Breast cancer genetic risk evaluation and referral for assessment." Journal of Clinical Oncology 31, no. 31_suppl (November 1, 2013): 75. http://dx.doi.org/10.1200/jco.2013.31.31_suppl.75.

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75 Background: ASCO Quality Oncology Practice Initiative (QOPI) provides tools for oncology practices to assess quality and adherence to clinical guidelines. Following each data submission a QOPI measures summary report is published providing practices the opportunity to compare themselves to QOPI Aggregates. In 2011, QOPI initiated a more stringent evaluation of family history documentation, which would improve rates of referral to genetic counseling for breast and colon cancer. Methods: A review of QOPI measure summary reports is performed by Rhode Island Hospital’s (RIH) Comprehensive Cancer Center Quality Improvement Team after each round of chart abstraction. Following review of QOPI practice results for genetic evaluation in 2011, our interventions included development and implementation of a 3 generation maternal and paternal family history intake form, genetics referral form with criteria to refer patients for genetic evaluation and initiation of a Genetics Clinic on site at the Cancer Center. Results: Presented is a summary of QOPI results for the Breast Cancer measures of complete family history documented and Genetic testing addressed appropriately. Conclusions: Our interventions included a patient intake form, genetics referral form with criteria to refer patients and a Genetics Clinic on site at the Cancer Center. The institution of a patient intake form resulted in a 19-fold improvement in complete family history documentation. The genetics referral form and establishment of an on-site Genetics clinic resulted in a 10% increase in referrals for genetic risk assessment. In spite of these interventions review of our Genetic Risk Evaluation data is notable for a 39% no show rate for the genetic risk assessment appointments. [Table: see text]

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Deckard, Jamalynne, Clement J. McDonald, and Daniel J. Vreeman. "Supporting interoperability of genetic data with LOINC." Journal of the American Medical Informatics Association 22, no. 3 (February 5, 2015): 621–27. http://dx.doi.org/10.1093/jamia/ocu012.

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Abstract Electronic reporting of genetic testing results is increasing, but they are often represented in diverse formats and naming conventions. Logical Observation Identifiers Names and Codes (LOINC) is a vocabulary standard that provides universal identifiers for laboratory tests and clinical observations. In genetics, LOINC provides codes to improve interoperability in the midst of reporting style transition, including codes for cytogenetic or mutation analysis tests, specific chromosomal alteration or mutation testing, and fully structured discrete genetic test reporting. LOINC terms follow the recommendations and nomenclature of other standards such as the Human Genome Organization Gene Nomenclature Committee’s terminology for gene names. In addition to the narrative text they report now, we recommend that laboratories always report as discrete variables chromosome analysis results, genetic variation(s) found, and genetic variation(s) tested for. By adopting and implementing data standards like LOINC, information systems can help care providers and researchers unlock the potential of genetic information for delivering more personalized care.

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Alexandrov, Alexander S. "FEUILLETONISTS’ CRITIQUE AND “MEDICAL TEXT” Abstract." Texts and History Journal of Philological Historical and Cultural Texts and History Studies 4 (2023): 120–26. http://dx.doi.org/10.31860/2712-7591-2023-4-120-126.

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This is a study of the use of medical text by Alexander A. Izmailov, Korney I. Chukovsky, and Alexander V. Amfiteatrov, leading Russian critics of the early 20th century, in feuilletons published in mass periodicals. The article considers two situations when critics used medical terminology in their critical responses to literary texts. One type of such a critique addressed literary texts that were related to medical issues and themselves contained medical terminology. In other cases, the use of medical terminology in critical responses was not called forth by the contents of the criticized texts. This study examines the reasons why the terminology associated with the practice of medicine became part of the critique. Moreover, this study reveals an evolution of the views of critics-feuilletonists on medical discourse and points out that this phenomenon gave rise to a serious dialogue between medicine and literature.

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DANYLYK, VITALII, VASYL LYTVYN, and SOLOMIYA MUSHASTA. "INFORMATION SYSTEM OF IDENTIFICATION OF TERMS AND ABBREVIATIONS IN TEXT DOCUMENTS." Herald of Khmelnytskyi National University. Technical sciences 319, no. 2 (April 27, 2023): 81–87. http://dx.doi.org/10.31891/2307-5732-2023-319-1-81-83.

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The paper examines the process of building and functioning of the system for identifying terms and abbreviations in text documents. The task of developing such a system is urgent, since such an identification problem often arises in the military sphere. During the implementation of the system, it was taken into account that a single term or abbreviation may have several explanations in different regulatory documents. All available explanations are added to the term or abbreviation, which is taken into account during the operation of the system. A feature of the system is the use of natural language processing methods, since terms can be found in different cases. To implement the system, ready-made Python packages were used to cover similar tasks: Tkinter, PyMuPDF Examples of the system’s functioning are given. The developed system is used in practice. In the process of completing the work, the research of problems and the search for solutions for the tasks is carried out, an information system is developed for the processing of documents with the aim of integrating definitions of potentially unknown terms and abbreviations into them, in order to enable officers to use any literature without problems, because all terms and abbreviations will be known. To generalize the documentation, all the necessary requirements for the system are defined, and in order to correctly create the architecture and allocate the functional tasks of the system under development, a system analysis is performed and a conceptual model is built. Using all the specified information, all the necessary diagrams are built using the UML notation. Diagrams depict the relationships between objects and the overall architecture of the system. The architecture of the system is built in such a way that the component systems and the system as a whole can be easily expanded. At the end of the development, testing and implementation of the project is carried out. The process of operation of the components of the system on the part of the end user and the process of deployment by the end user of the information system are described. The object of the study is the presence of slowing factors in the process of command and control carried out by commanders of tactical units, which can slow down decision-making and also affect their correctness. The subject of the study is to solve the problems of the appearance of slowing factors in the process of command and control carried out by commanders of tactical units, by means of work with military data.

45

Best, Michael L. "An Ecology of Text: Using Text Retrieval to Study Alife on the Net." Artificial Life 3, no. 4 (October 1997): 261–87. http://dx.doi.org/10.1162/artl.1997.3.4.261.

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I introduce a new alife model, an ecology based on a corpus of text, and apply it to the analysis of posts to USENET News. In this corporal ecology posts are organisms, the newsgroups of NetNews define an environment, and human posters situated in their wider context make up a scarce resource. I apply latent semantic indexing (LSI), a text retrieval method based on principal component analysis, to distill from the corpus those replicating units of text. LSI arrives at suitable replicators because it discovers word co-occurrences that segregate and recombine with appreciable frequency. I argue that natural selection is necessarily in operation because sufficient conditions for its occurrence are met: replication, mutagenicity, and trait/fitness covariance. I describe a set of experiments performed on a static corpus of over 10,000 posts. In these experiments I study average population fitness, a fundamental element of population ecology. My study of fitness arrives at the tinhappy discovery that a flame-war, centered around an overly prolific poster, is the king of the jungle.

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Rebholz-Schuhmann, Dietrich, Harald Kirsch, and Francisco Couto. "Facts from Text—Is Text Mining Ready to Deliver?" PLoS Biology 3, no. 2 (February 15, 2005): e65. http://dx.doi.org/10.1371/journal.pbio.0030065.

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Blaschke, Christian, Alexander Yeh, Lynette Hirschman, and Alfonso Valencia. "ISMB 2003 Text Mining SIG Meeting Report." Comparative and Functional Genomics 4, no. 6 (2003): 667–73. http://dx.doi.org/10.1002/cfg.338.

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Ongenaert, M., L. Van Neste, T. De Meyer, G. Menschaert, S. Bekaert, and W. Van Criekinge. "PubMeth: a cancer methylation database combining text-mining and expert annotation." Nucleic Acids Research 36, Database (December 23, 2007): D842—D846. http://dx.doi.org/10.1093/nar/gkm788.

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Kim, S., S. Y. Shin, I. H. Lee, S. J. Kim, R. Sriram, and B. T. Zhang. "PIE: an online prediction system for protein-protein interactions from text." Nucleic Acids Research 36, Web Server (May 19, 2008): W411—W415. http://dx.doi.org/10.1093/nar/gkn281.

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Ruíz-de-Almirón-de-Andrés, B. "La genética en la medicina actual: problemas que plantean los test genéticos de consumo difundido." ACTUALIDAD MEDICA 105, no. 105(810) (August 31, 2020): 128. http://dx.doi.org/10.15568/am.2020.810.cd01.

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