knowledge graph
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Contemporary bioinformatic and chemoinformatic capabilities hold promise to reshape knowledge management, analysis and interpretation of data in natural products research. Currently, reliance on a disparate set of non-standardized, insular, and specialized databases presents a series of challenges for data access, both within the discipline and for integration and interoperability between related fields. The fundamental elements of exchange are referenced structure-organism pairs that establish relationships between distinct molecular structures and the living organisms from which they were identified. Consolidating and sharing such information via an open platform has strong transformative potential for natural products research and beyond. This is the ultimate goal of the newly established LOTUS initiative, which has now completed the first steps toward the harmonization, curation, validation and open dissemination of 750,000+ referenced structure-organism pairs. LOTUS data is hosted on Wikidata and regularly mirrored on https://lotus.naturalproducts.net. Data sharing within the Wikidata framework broadens data access and interoperability, opening new possibilities for community curation and evolving publication models. Furthermore, embedding LOTUS data into the vast Wikidata knowledge graph will facilitate new biological and chemical insights. The LOTUS initiative represents an important advancement in the design and deployment of a comprehensive and collaborative natural products knowledge base.
Phosphorylation of specific substrates by protein kinases is a key control mechanism for vital cell-fate decisions and other cellular processes. However, discovering specific kinase-substrate relationships is time-consuming and often rather serendipitous. Computational predictions alleviate these challenges, but the current approaches suffer from limitations like restricted kinome coverage and inaccuracy. They also typically utilise only local features without reflecting broader interaction context. To address these limitations, we have developed an alternative predictive model. It uses statistical relational learning on top of phosphorylation networks interpreted as knowledge graphs, a simple yet robust model for representing networked knowledge. Compared to a representative selection of six existing systems, our model has the highest kinome coverage and produces biologically valid high-confidence predictions not possible with the other tools. Specifically, we have experimentally validated predictions of previously unknown phosphorylations by the LATS1, AKT1, PKA and MST2 kinases in human. Thus, our tool is useful for focusing phosphoproteomic experiments, and facilitates the discovery of new phosphorylation reactions. Our model can be accessed publicly via an easy-to-use web interface (LinkPhinder).
BACKGROUND: Protein-protein interactions (PPI) play a key role in an investigation of various biochemical processes, and their identification is thus of great importance. Although computational prediction of which amino acids take part in a PPI has been an active field of research for some time, the quality of in-silico methods is still far from perfect. RESULTS: We have developed a novel prediction method called INSPiRE which benefits from a knowledge base built from data available in Protein Data Bank. All proteins involved in PPIs were converted into labeled graphs with nodes corresponding to amino acids and edges to pairs of neighboring amino acids. A structural neighborhood of each node was then encoded into a bit string and stored in the knowledge base. When predicting PPIs, INSPiRE labels amino acids of unknown proteins as interface or non-interface based on how often their structural neighborhood appears as interface or non-interface in the knowledge base. We evaluated INSPiRE's behavior with respect to different types and sizes of the structural neighborhood. Furthermore, we examined the suitability of several different features for labeling the nodes. Our evaluations showed that INSPiRE clearly outperforms existing methods with respect to Matthews correlation coefficient. CONCLUSION: In this paper we introduce a new knowledge-based method for identification of protein-protein interaction sites called INSPiRE. Its knowledge base utilizes structural patterns of known interaction sites in the Protein Data Bank which are then used for PPI prediction. Extensive experiments on several well-established datasets show that INSPiRE significantly surpasses existing PPI approaches.
Robust scientific knowledge is contingent upon replication of original findings. However, replicating researchers are constrained by resources, and will almost always have to choose one replication effort to focus on from a set of potential candidates. To select a candidate efficiently in these cases, we need methods for deciding which out of all candidates considered would be the most useful to replicate, given some overall goal researchers wish to achieve. In this article we assume that the overall goal researchers wish to achieve is to maximize the utility gained by conducting the replication study. We then propose a general rule for study selection in replication research based on the replication value of the set of claims considered for replication. The replication value of a claim is defined as the maximum expected utility we could gain by conducting a replication of the claim, and is a function of (a) the value of being certain about the claim, and (b) uncertainty about the claim based on current evidence. We formalize this definition in terms of a causal decision model, utilizing concepts from decision theory and causal graph modeling. We discuss the validity of using replication value as a measure of expected utility gain, and we suggest approaches for deriving quantitative estimates of replication value. Our goal in this article is not to define concrete guidelines for study selection, but to provide the necessary theoretical foundations on which such concrete guidelines could be built. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
- MeSH
- lidé MeSH
- nejistota MeSH
- teoretické modely * MeSH
- znalosti * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Tracking motile cells in time-lapse series is challenging and is required in many biomedical applications. Cell tracks can be mathematically represented as acyclic oriented graphs. Their vertices describe the spatio-temporal locations of individual cells, whereas the edges represent temporal relationships between them. Such a representation maintains the knowledge of all important cellular events within a captured field of view, such as migration, division, death, and transit through the field of view. The increasing number of cell tracking algorithms calls for comparison of their performance. However, the lack of a standardized cell tracking accuracy measure makes the comparison impracticable. This paper defines and evaluates an accuracy measure for objective and systematic benchmarking of cell tracking algorithms. The measure assumes the existence of a ground-truth reference, and assesses how difficult it is to transform a computed graph into the reference one. The difficulty is measured as a weighted sum of the lowest number of graph operations, such as split, delete, and add a vertex and delete, add, and alter the semantics of an edge, needed to make the graphs identical. The measure behavior is extensively analyzed based on the tracking results provided by the participants of the first Cell Tracking Challenge hosted by the 2013 IEEE International Symposium on Biomedical Imaging. We demonstrate the robustness and stability of the measure against small changes in the choice of weights for diverse cell tracking algorithms and fluorescence microscopy datasets. As the measure penalizes all possible errors in the tracking results and is easy to compute, it may especially help developers and analysts to tune their algorithms according to their needs.
Computer assisted image acquisition techniques, including confocal microscopy, require efficient tools for an automatic sorting of vast amount of generated image data. The complexity of the classification process, absence of adequate tools, and insufficient amount of reference data has made the automated processing of images challenging. Mastering of this issue would allow implementation of statistical analysis in research areas such as in research on formation of t-tubules in cardiac myocytes. We developed a system aimed at automatic assessment of cardiomyocyte development stages (SAACS). The system classifies confocal images of cardiomyocytes with fluorescent dye stained sarcolemma. We based SAACS on a densely connected convolutional network (DenseNet) topology. We created a set of labelled source images, proposed an appropriate data augmentation technique and designed a class probability graph. We showed that the DenseNet topology, in combination with the augmentation technique is suitable for the given task, and that high-resolution images are instrumental for image categorization. SAACS, in combination with the automatic high-throughput confocal imaging, will allow application of statistical analysis in the research of the tubular system development or remodelling and loss.
- MeSH
- buněčná diferenciace MeSH
- fluorescenční barviva MeSH
- kardiomyocyty cytologie ultrastruktura MeSH
- konfokální mikroskopie metody MeSH
- krysa rodu rattus MeSH
- modely kardiovaskulární MeSH
- neuronové sítě MeSH
- počítačové zpracování obrazu metody MeSH
- sarkolema ultrastruktura MeSH
- strojové učení MeSH
- umělá inteligence MeSH
- zvířata MeSH
- Check Tag
- krysa rodu rattus MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Východisko: Výzkum byl zaměřen na identifikaci postojů občanů ČR k některým aspektům činnosti praktických lékařů. Publikace navazuje na a předchozí výstupy z let 2015–2022 a v roce 2023 byla zaměřena zejména na vybrané otázky z IT problematiky. Cíl a metody: Cílem bylo zjistit, jak občané hodnotí čas a péči, kterou jim praktický lékař věnuje, a jaké je jejich stanovisko k práci zdravotní sestry v ordinaci jejich praktického lékaře. V rámci výzkumu byly rovněž sledovány otázky týkající se využívání prvků umělé inteligence v práci praktického lékaře, možnosti objednání jeho pacientů k vyšetření na konkrétní dobu, a pokud ano, zda tak lze učinit nějakým elektronickým systémem. Zjišťováno bylo rovněž, zda praktický lékař používá elektronickou, nebo papírovou dokumentaci a v kolika procentech by maximálně měl dle mínění občanů praktický lékař ordinovat „na dálku“ (tzv. telemedicína). Otázky byly rovněž zaměřeny na to, zda by měl mít praktický lékař přístup k výsledkům pacienta či zprávám z nemocnice, kdykoliv to potřebuje, prostřednictvím elektronického úložiště, který lékař by měl mít automaticky přístup ke zdravotním informacím respondenta a zda se občané domnívají, že jejich zdravotní data jsou dobře zabezpečena. Dotazovaný soubor je reprezentativním vzorkem populace České republiky ve věku 15 a více let. Statistické zpracování dat bylo provedeno programem SASD 1.5.8. (Statistická analýza sociálních dat). Zpracován byl 1. stupeň třídění a kontingenční tabulky vybraných ukazatelů 2. stupně třídění. Míra závislosti vybraných znaků byla stanovena na základě χ2 testu nezávislosti a dalších testovacích kritérií aplikovaných dle charakteru rozdělení znaků. Na základě této analýzy byla provedena interpretace dat a zpracovány příslušné tabulky a grafy. Výsledky: Občané ČR jsou ve většině případů (94 %) s péčí a časem, který jim věnuje v průběhu jejich návštěvy praktický lékař, spokojeni, negativní stanovisko zaujímá jen malá část (6,0 %) z nich. Největší spokojenost s péčí praktického lékaře a časem, který jim věnuje, se vrátila na úroveň let 2018–2020, tj. na úroveň před pandemií COVID-19. Největší část občanů ČR (37,0 %) by v současné době byla proti tomu, aby jejich praktický lékař využíval ve své práci prvky umělé inteligence. Souhlasné stanovisko vyjádřilo jen 29,2 % dotázaných. Celkem 70,7 % občanů má již možnost v případě potřeby se ke svému praktickému lékaři objednat na konkrétní dobu prostřednictvím nějakého elektronického systému. Též 55,1 % občanů připouští nějaký rozsah ordinování jejich praktického lékaře „na dálku“ (telemedicína). Jednoznačně platí, že občané ČR cca v 70 % souhlasí s tím, aby měl jejich praktický lékař kdykoliv přístup k jejich zdravotním datům, a 39,8 % se domnívá, že jejich zdravotní data jsou dobře zabezpečena zejména u praktického lékaře.
Background: The research was aimed at identifying the attitudes of Czech citizens towards certain aspects of the activities of general practitioners. The publication builds on previous outputs from 2015–2022 and in 2023 it focused mainly on selected issues from the sphere of IT. Aim and methods: The aim was to determine how citizens evaluated the time and care provided by their general practitioner and what they thought of the nurse’s work in their GP’s office. The research also investigated questions concerning the use of artificial intelligence elements in the GP’s work, the option of making appointments for patients to be seen at specific times, and, if so, whether an electronic system could do this. It also investigated whether the GP used electronic or paper documentation and what maximum percentage of "remote" practice (telemedicine) should be conducted by the GP, in the citizens’ opinion. Questions also focused on whether a GP should be able to access patient results or hospital reports whenever he or she needed to do so via an e-repository, which doctors should automatically have access to the respondent’s health information, and whether citizens believed that their health data were well secured. The survey respondents are a representative sample of the population of the Czech Republic aged 15 and over. The statistical data processing was performed with the SASD 1.5.8 (Statistical Analysis of Social Data) programme. The first classification level and the contingency tables of selected indicators of the second classification level were prepared. The degree of dependence of the selected traits was determined based on the χ2 test of independence and other test criteria, applied according to the nature of the distribution of traits. Based on this analysis, the data were interpreted, and the corresponding tables and graphs were prepared. Results: Czech citizens are mostly (94%) satisfied with the care and time provided to them during their visit by a general practitioner; only a small proportion (6.0%) of them have a negative opinion. The highest satisfaction with the care and time given by their GP has returned to 2018–2020 levels, i.e. to pre-Covid-19 pandemic levels. The largest proportion of Czech citizens (37.0%) would currently be against their GP using AI elements in their work. Only 29.2% of the respondents expressed a favourable opinion. A total of 70.7% of citizens are already able to make an appointment with their GP for a specific time via an electronic system if necessary. Also, 55.1% of citizens admit to some extent of their GP’s practice being conducted "remotely" (telemedicine). Clearly, approximately 70% of Czech citizens agree that their GP should have access to their health data at any time and 39.8% believe that their health data are well secured, especially by their GP.
- MeSH
- lidé MeSH
- praktičtí lékaři MeSH
- primární zdravotní péče * MeSH
- sběr dat MeSH
- spokojenost pacientů * MeSH
- umělá inteligence MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- grafy a diagramy MeSH
- Geografické názvy
- Česká republika MeSH
Vzhledem ke vzrůstajícímu počtu obyvatel Čínské lidové republiky a současným globalizačním tendencím společnosti, nevyjímajíce obyvatele ČLR, je jistě potřebné, abychom v odborné ošetřovatelské veřejnosti znali alespoň základní informace o příslušnících čínské minoritní skupiny žijící v ČR a jejich specifika v oblasti ošetřovatelské péče. Tato výzkumná práce je zpracována pomocí metod kvalitativního výzkumu. Výzkumným cílem této práce bylo zpracovat zvláštnosti ošetřovatelské péče, které si příslušníci čínské menšiny přejí respektovat. Sběr dat byl proveden pomocí polostruktorovaného rozhovoru u příslušníků čínské minoritní skupiny v ČR. Obsah otázek použitého polostrukturovaného rozhovoru vychází zejména z koncepčních ošetřovatelských modelů M. Gordonové, M. Leiningerové a modelu J. Gigerové – R. Davidhizerové. K dosažení cíle bylo stanoveno pět výzkumných otázek. Na základě výsledků rozhovorů jsou vytvořeny kazuistiky. Kazuistiky tvoří výzkumný podklad, ze kterého vycházejí kategorizované tabulky a grafy (modifikovaný přístup rámcové analýzy), v nichž jsou sumarizovány nejdůležitější výsledky výzkumu. K hlavním výsledkům řadíme zjištěné zvláštnosti ošetřovatelské péče v oblasti odběrů krve, sdělování lékařské diagnózy obvšichzvláště rodině, obavy ze závislosti na lécích a také bolest a její řešení. K dalším výsledkům patří také popis toho, jak vnímají příslušníci čínské minoritní skupiny české ošetřovatelství a sestru jako poskytovatelku odborné ošetřovatelské péče. Na základě výsledků práce jsou navrženy hypotézy určené k dalšímu výzkumnému využití. Základní informace o příslušnících čínské minoritní skupiny žijící v ČR jsme zpracovali do informačního sumáře a do standardu ošetřovatelské péče. Každý z nás při kontaktu s ošetřovatelským personálem očekává kvalitní, individuální a ohleduplnou péči. Je nutné respektovat specifika všech pacientů bez ohledu na barvu pleti, politické či spirituální vyznání. Je vhodné se v době poskytování profesionální ošetřovatelské péče „povznést“ nad hranice své vlastní kultury a zvyklosti s cílem poskytnutí co nejefektivnější ošetřovatelské péče našemu pacientovi/ klientovi z jakékoliv kultury.
Given the increasing number of inhabitants of the People´s Republic of China and contemporary globalisation tendencies in the society including inhabitants of this Republic, it is of course necessary to know at least principal information concerning members of the Chinese minority living in the Czech Republic and their specific features in the field of nursing care. This research work was elaborated with the use of qualitative research methods. The research target of the present work was to consider special features of the nursing care, which should be respected according to the members of the Chinese minority. The data accumulation was provided with the help of semi-structured interviews with members of the Chinese minority group in the Czech Republic. The scope of questions of the semi-structured interview used is particularly based on conceptual nursing models by M. Gordon, M. Leininger and a model by J. Giger – R. Davidhizer. To achieve this target, five research questions were established. Case reports were obtained based on results of the interviews. The case reports form a research basis for categorized tables and graphs (modified approach of framework analysis), where most important research results are summarized. The main results include the determined specific features of the nursing care in the field of sampling the blood, communicating medical diagnosis, particularly for the family, fear of drug dependence and also pain and its solution. Further results also include a description of the perception of Czech nursing and nurses as providers of the special nursing care by members of the Chinese minority group. Based on the results of the work, hypotheses are proposed, designed for the further research. The principal data concerning members of the Chinese minority group living in the Czech Republic were arranged in an information summary and standards of nursing care. In contact with nursing personnel, everybody of us expects quality individual and respectful care. It is necessary to respect specific features of all the patients regardless of the colour of the skin and political or spiritual creed. When granting the professional nursing care, it is necessary to rise above limits of our own culture and habits with the aim to provide our patient/client from any cultural group with as effective nursing care as possible.
- MeSH
- bolest farmakoterapie psychologie MeSH
- komunikace MeSH
- lidé MeSH
- management bolesti MeSH
- menšiny psychologie MeSH
- ošetřovatelská péče metody využití MeSH
- práva pacientů MeSH
- rozhovory jako téma MeSH
- sdělení pravdy MeSH
- vztahy mezi ošetřovatelkou a pacientem etika MeSH
- zdraví - znalosti, postoje, praxe MeSH
- zdravotní stav MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- kazuistiky MeSH
- Geografické názvy
- Česká republika MeSH
- Čína MeSH
new approach to the segmentation of 3D CT images is proposed in an attempt to provide texture-based segmentation of organs or disease diagnosis. 3D extension of Haralick texture features was studied calculating co-occurrences of all voxels in a small cubic region around the voxel. RESULTS: For verification, the proposed method was tested on a set of abdominal 3D volumes of patients. Statistically, the improvement in segmentation was significant for most of the organs considered herein. CONCLUSIONS: The proposed method has potential application in medical image segmentation, including diagnosis of diseases.
- MeSH
- algoritmy MeSH
- lidé MeSH
- počítačová rentgenová tomografie metody MeSH
- rentgendiagnostika břicha metody MeSH
- rentgenový obraz - interpretace počítačová metody MeSH
- reprodukovatelnost výsledků MeSH
- rozpoznávání automatizované metody MeSH
- senzitivita a specificita MeSH
- umělá inteligence MeSH
- vylepšení rentgenového snímku metody MeSH
- zobrazování trojrozměrné metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- práce podpořená grantem MeSH
... A graph-grammar approach to represent causal, temporal and other contexts in an oncological patient record ... ... Collaborative knowledge processing. ... ... A graph conceptual model for developing Human Genome Center databases. ... ... Evaluation of automatic knowledge acquisition techniques in the diagnosis of acute abdominal pain. ... ... Evaluation of a knowledge-based system providing ventilatory management and decision for extubation. ...
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- MeSH
- chorobopisy - počítačové systémy MeSH
- management znalostí MeSH
- metody pro podporu rozhodování MeSH
- mezisektorová spolupráce MeSH
- počítačové zpracování obrazu MeSH
- počítačové zpracování signálu MeSH
- řízení zdravotnictví MeSH
- studium lékařství MeSH
- zdravotnické informační systémy MeSH
- Publikační typ
- souborné dílo MeSH
- Konspekt
- Lékařské vědy. Lékařství
- NLK Obory
- lékařská informatika
- NLK Publikační typ
- ročenky