scholarly journals Classification of Tumor Samples from Expression Data Using Decision Trunks

2013 ◽  
Vol 12 ◽  
pp. CIN.S10356 ◽  
Author(s):  
Benjamin Ulfenborg ◽  
Karin Klinga-Levan ◽  
Björn Olsson
Keyword(s):  
Decision Trees ◽  
Comprehensive Evaluation ◽  
Expression Data ◽  
Current State ◽  
Wide Range ◽  
Machine Learning Approach ◽  
Human Decision ◽  
Classification Tasks ◽  
Testing Practices

We present a novel machine learning approach for the classification of cancer samples using expression data. We refer to the method as “decision trunks,” since it is loosely based on decision trees, but contains several modifications designed to achieve an algorithm that: (1) produces smaller and more easily interpretable classifiers than decision trees; (2) is more robust in varying application scenarios; and (3) achieves higher classification accuracy. The decision trunk algorithm has been implemented and tested on 26 classification tasks, covering a wide range of cancer forms, experimental methods, and classification scenarios. This comprehensive evaluation indicates that the proposed algorithm performs at least as well as the current state of the art algorithms in terms of accuracy, while producing classifiers that include on average only 2–3 markers. We suggest that the resulting decision trunks have clear advantages over other classifiers due to their transparency, interpretability, and their correspondence with human decision-making and clinical testing practices.

scholarly journals Classification of non-coding variants with high pathogenic impact

2021 ◽  
Author(s):  
Lambert Moyon ◽  
Camille Berthelot ◽  
Alexandra Louis ◽  
Nga Thi Thuy Nguyen ◽  
Hugues Roest Crollius
Keyword(s):  
Personalised Medicine ◽  
Clinical Settings ◽  
Functional Interpretation ◽  
Protein Coding ◽  
Wide Range ◽  
Machine Learning Approach ◽  
Functional Consequences ◽  
Control Optimisation ◽  
Coding Variants

Whole genome sequencing is increasingly used to diagnose medical conditions of genetic origin. While both coding and non-coding DNA variants contribute to a wide range of diseases, most patients who receive a WGS-based diagnosis today harbour a protein-coding mutation. Functional interpretation and prioritization of non-coding variants represents a persistent challenge, and disease-causing non-coding variants remain largely unidentified. Depending on the disease, WGS fails to identify a candidate variant in 20-80% of patients, severely limiting the usefulness of sequencing for personalised medicine. Here we present FINSURF, a machine-learning approach to predict the functional impact of non-coding variants in regulatory regions. FINSURF outperforms state-of-the-art methods, owing to control optimisation during training. In addition to ranking candidate variants, FINSURF also delivers diagnostic information on functional consequences of mutations. We applied FINSURF to a diverse set of 30 diseases with described causative non-coding mutations, and correctly identified the disease-causative non-coding variant within the ten top hits in 22 cases. FINSURF is implemented as an online server to as well as custom browser tracks, and provides a quick and efficient solution to prioritize candidate non-coding variants in realistic clinical settings.

scholarly journals Classification and analysis of measuring transducers of intensity (induction) of alternating magnetic fields

2021 ◽  
pp. 82-93
Author(s):  
Yurii Bobkov
Keyword(s):  
Magnetic Fields ◽  
Magnetic Measurements ◽  
Advantages And Disadvantages ◽  
Current State ◽  
Primary Measuring ◽  
Wide Range ◽  
The Right ◽  
Physical Phenomena ◽  
Alternating Magnetic Fields

The current state of technology is characterized by the mass use of electricity, the use of various electrical, electronic and radio devices. This causes expansion of magnetic measurements and the need to develop new highly sensitive measuring equipment for a wide range of frequencies. One of its main elements, that largely determines the accuracy, frequency and dynamic ranges, are the primary measuring sensors of strength (induction) of alternating magnetic fields. Many works have been devoted to the analysis and development of various sensors of strength (induction) of magnetic fields. At the same time, it can be noted the lack of a systematic approach to the measurement of alternating magnetic fields. The problem of the general classification of methods of measurement of alternating magnetic fields and, accordingly, primary measuring sensors of strength (induction) of alternating magnetic fields is not solved. In most cases, separate issues of measuring alternating magnetic fields and certain types of sensors are considered. That does not allow obtaining a holistic picture in this area and make the right choice of direction for solving assigned tasks. The comprehensive analysis of methods of measuring alternating magnetic fields was carried out in this work. Based on it, the classification of primary measuring sensors of strength (induction) of alternating magnetic fields, on the physical principles of transformation was proposed. Accordingly, the available measuring sensors of alternating magnetic fields following to the group of used physical phenomena can be divided into: magnetomechanical, induction, galvanomagnetic, quantum, magneto-optical and photomagnetic. Depending on the characteristics of each of these phenomena, separate measurement methods and types of measuring sensors were highlighted. The current state of development of each of the types of measuring sensors of strength of alternating magnetic fields was analyzed, their advantages and disadvantages were determined, the limits of dynamic and frequency ranges, the maximum values of errors were outlined. The obtained results allow to significantly simplify and reduce the time of choosing the necessary method of strength (induction) of alternating magnetic fields measuring and to choose the necessary type of measuring sensor to effectively solve the tasks.

The current state of the legislative implementation of criminal law policy

2020 ◽  
pp. 111-118
Author(s):  
Oleksandr Ostrohliad
Keyword(s):  
Law Enforcement ◽  
Criminal Code ◽  
Practical Significance ◽  
New Approach ◽  
Public Discussion ◽  
Current State ◽  
Criminal Offenses ◽  
Legal Technology ◽  
Logical Semantic

Purpose. The aim of the work is to consider the novelties of the legislative work, which provide for the concept and classification of criminal offenses in accordance with the current edition of the Criminal Code of Ukraine and the draft of the new Code developed by the working group and put up for public discussion. Point out the gaps in the current legislation and the need to revise individual rules of the project in this aspect. The methodology. The methodology includes a comprehensive analysis and generalization of the available scientific and theoretical material and the formulation of appropriate conclusions and recommendations. During the research, the following methods of scientific knowledge were used: terminological, logical-semantic, system-structural, logical-normative, comparative-historical. Results In the course of the study, it was determined that despite the fact that the amendments to the Criminal Code of Ukraine came into force in July of this year, their perfection, in terms of legal technology, raises many objections. On the basis of a comparative study, it was determined that the Draft Criminal Code of Ukraine needs further revision taking into account the opinions of experts in the process of public discussion. Originality. In the course of the study, it was established that the classification of criminal offenses proposed in the new edition of the Criminal Code of Ukraine does not stand up to criticism, since other elements of the classification appear in subsequent articles, which are not covered by the existing one. The draft Code, using a qualitatively new approach to this issue, retains the elements of the previous classification and has no practical significance in law enforcement. Practical significance. The results of the study can be used in law-making activities to improve the norms of the current Criminal Code, to classify criminal offenses, as well as to further improve the draft Criminal Code of Ukraine.

A Brief Survey on Text Classification Using Various Machine Learning Techniques

2018 ◽  
Vol 8 (1) ◽  
pp. 14
Author(s):  
Padmavathi .S ◽  
M. Chidambaram
Keyword(s):  
Machine Learning ◽  
Text Classification ◽  
Fixed Number ◽  
Machine Learning Techniques ◽  
Online Information ◽  
Rule Based ◽  
Learning Techniques ◽  
Machine Learning Approach ◽  
Rule Based Approach

Text classification has grown into more significant in managing and organizing the text data due to tremendous growth of online information. It does classification of documents in to fixed number of predefined categories. Rule based approach and Machine learning approach are the two ways of text classification. In rule based approach, classification of documents is done based on manually defined rules. In Machine learning based approach, classification rules or classifier are defined automatically using example documents. It has higher recall and quick process. This paper shows an investigation on text classification utilizing different machine learning techniques.

Young Scholars Conference “Slavic World: Commonality and Diversity”. 21–22 May 2019. Session “Linguistics”

2019 ◽  
Vol 14 (1-2) ◽  
pp. 295-297
Author(s):  
Sergej A. Borisov
Keyword(s):  
Czech Republic ◽  
Middle Ages ◽  
The Czech Republic ◽  
International Context ◽  
Slavic Languages ◽  
Russian Academy Of Sciences ◽  
Current State ◽  
Wide Range ◽  
History Of ◽  
Academy Of Sciences

For more than twenty years, the Institute of Slavic Studies of the Russian Academy of Sciences celebrates the Day of Slavic Writing and Culture with a traditional scholarly conference.”. Since 2014, it has been held in the young scholars’ format. In 2019, participants from Moscow, St. Petersburg, Kazan, Togliatti, Tyumen, Yekaterinburg, and Rostov-on-Don, as well as Slovakia, the Czech Republic, Hungary, and Romania continued this tradition. A wide range of problems related to the history of the Slavic peoples from the Middle Ages to the present time in the national, regional and international context were discussed again. Participants talked about the typology of Slavic languages and dialects, linguo-geography, socio- and ethnolinguistics, analyzed formation, development, current state, and prospects of Slavic literatures, etc.

REFLECTION OF THE CURRENT STATE OF PUBLICISTIC JOURNALISM GENRES IN THE SLOVAK MEDIA ENVIRONMENT

2020 ◽  
Author(s):  
Zuzana Kvetanová
Keyword(s):  
Discourse Analysis ◽  
Point Of View ◽  
Media Theory ◽  
Logical Analysis ◽  
Periodical Press ◽  
Media Environment ◽  
Current State ◽  
Journalistic Practice ◽  
Opinion Journalism

The submitted study addresses the topic of the current state of the opinion journalism and its genres in the Slovak periodical press. The author draws attention to the question of classification of the opinion journalism of a rational and emotional type from the genre categorization point of view and, simultaneously, reflects on its application in the present journalistic practice. This brings a certain rate of confrontation between the defined theoretical premises and their subsequent practical (non-)implementation. The main objective of the study is to clarify the presence of genres of analytical and literary opinion journalism stated by media theory in the environment of the Slovak periodicals. Presentation of the basic terminological axis and the related explication of journalism genres included in the opinion journalism constitute the secondary objectives of the paper. For the purposes of achieving the set objectives, the author uses methods of logical analysis of text in combination with discourse analysis. Similarly, she predicts the evident presence of the phenomenon of hybridization in the Slovak journalistic practice.

scholarly journals Toxic or Not Toxic, That Is the Carbon Quantum Dot’s Question: A Comprehensive Evaluation with Zebrafish Embryo, Eleutheroembryo, and Adult Models

Polymers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1598
Author(s):  
Chih-Yu Chung ◽  
Yu-Ju Chen ◽  
Chia-Hui Kang ◽  
Hung-Yun Lin ◽  
Chih-Ching Huang ◽  
...  
Keyword(s):  
Zebrafish Embryo ◽  
Comprehensive Evaluation ◽  
Aquatic Organisms ◽  
Carbon Quantum Dots ◽  
Adult Zebrafish ◽  
Fish Embryo ◽  
Wide Range ◽  
Different Types ◽  
Low Toxicity

Carbon quantum dots (CQDs) are emerging novel nanomaterials with a wide range of applications and high biocompatibility. However, there is a lack of in-depth research on whether CQDs can cause acute or long-term adverse reactions in aquatic organisms. In this study, two different types of CQDs prepared by ammonia citrate and spermidine, namely CQDAC and CQDSpd, were used to evaluate their biocompatibilities. In the fish embryo acute toxicity test (FET), the LD50 of CQDAC and CQDSpd was about 500 and 100 ppm. During the stage of eleutheroembryo, the LD50 decreased to 340 and 55 ppm, respectively. However, both CQDs were quickly eliminated from embryo and eleutheroembryo, indicating a lack of bioaccumulation. Long-term accumulation of CQDs was also performed in this study, and adult zebrafish showed no adverse effects in 12 weeks. In addition, there was no difference in the hatchability and deformity rates of offspring produced by adult zebrafish, regardless of whether they were fed CQDs or not. The results showed that both CQDAC and CQDSpd have low toxicity and bioaccumulation to zebrafish. Moreover, the toxicity assay developed in this study provides a comprehensive platform to assess the impacts of CQDs on aquatic organisms in the future.

scholarly journals A Machine Learning Approach to Study Glycosidase Activities from Bifidobacterium

2021 ◽  
Vol 9 (5) ◽  
pp. 1034
Author(s):  
Carlos Sabater ◽  
Lorena Ruiz ◽  
Abelardo Margolles
Keyword(s):  
Machine Learning ◽  
Supervised Classification ◽  
Machine Learning Algorithms ◽  
Learning Approach ◽  
Human Milk Oligosaccharides ◽  
Future Studies ◽  
High Fiber ◽  
Machine Learning Approach ◽  
Prebiotic Oligosaccharides

This study aimed to recover metagenome-assembled genomes (MAGs) from human fecal samples to characterize the glycosidase profiles of Bifidobacterium species exposed to different prebiotic oligosaccharides (galacto-oligosaccharides, fructo-oligosaccharides and human milk oligosaccharides, HMOs) as well as high-fiber diets. A total of 1806 MAGs were recovered from 487 infant and adult metagenomes. Unsupervised and supervised classification of glycosidases codified in MAGs using machine-learning algorithms allowed establishing characteristic hydrolytic profiles for B. adolescentis, B. bifidum, B. breve, B. longum and B. pseudocatenulatum, yielding classification rates above 90%. Glycosidase families GH5 44, GH32, and GH110 were characteristic of B. bifidum. The presence or absence of GH1, GH2, GH5 and GH20 was characteristic of B. adolescentis, B. breve and B. pseudocatenulatum, while families GH1 and GH30 were relevant in MAGs from B. longum. These characteristic profiles allowed discriminating bifidobacteria regardless of prebiotic exposure. Correlation analysis of glycosidase activities suggests strong associations between glycosidase families comprising HMOs-degrading enzymes, which are often found in MAGs from the same species. Mathematical models here proposed may contribute to a better understanding of the carbohydrate metabolism of some common bifidobacteria species and could be extrapolated to other microorganisms of interest in future studies.

scholarly journals Modes of Interaction in Naturally Occurring Medical Encounters With General Practitioners: The “One in a Million” Study

2021 ◽  
pp. 104973232199379
Author(s):  
Olaug S. Lian ◽  
Sarah Nettleton ◽  
Åge Wifstad ◽  
Christopher Dowrick
Keyword(s):  
General Practitioners ◽  
Narrative Analysis ◽  
Mode Competition ◽  
General Applicability ◽  
Naturally Occurring ◽  
Wide Range ◽  
The One ◽  
Narrative Mode ◽  
Modes Of Interaction

In this article, we qualitatively explore the manner and style in which medical encounters between patients and general practitioners (GPs) are mutually conducted, as exhibited in situ in 10 consultations sourced from the One in a Million: Primary Care Consultations Archive in England. Our main objectives are to identify interactional modes, to develop a classification of these modes, and to uncover how modes emerge and shift both within and between consultations. Deploying an interactional perspective and a thematic and narrative analysis of consultation transcripts, we identified five distinctive interactional modes: question and answer (Q&A) mode, lecture mode, probabilistic mode, competition mode, and narrative mode. Most modes are GP-led. Mode shifts within consultations generally map on to the chronology of the medical encounter. Patient-led narrative modes are initiated by patients themselves, which demonstrates agency. Our classification of modes derives from complete naturally occurring consultations, covering a wide range of symptoms, and may have general applicability.

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