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会议名称:

International Conference on Information Technology in Bio- and Medical Informatics

召开年:

2015

召开地:

Valencia

会议文集:

Information technology in bio- and medical informatics: 6th International Conference, ITBAM 2015, Valencia, Spain, September 3-4, 2015, Proceedings

主办单位:

Springer

出版时间:

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  • 题名 作者 来源 发表时间 操作
  • IT in Biology & Medical Informatics: On the Challenge of Understanding the Data Ecosystem

    作者:Andreas Holzinger;Miroslav Bursa;Sami Khuri;M. Elena Renda; 会议名称:International conference on information technology in bio- and medical informatics 2017年

    Data intensive disciplines, such as life sciences and medicine, are promoting vivid research activities in the area of data science. Modern technologies, such as high-throughput mass-spectrometry and sequencing, micro-arrays, high-resolution imaging, etc., produce enormous and continuously increasing amounts of data. Huge public databases provide access to aggregated and consolidated data on genome and protein sequences, biological pathways, diseases, anatomy atlases, and scientific literature. There has never been before more potentially available data to study biomedical systems, ranging from single cells to complete organisms. However, it is a non-trivial task to transform the vast amount of biomedical data into actionable, useful and usable information, triggering scientific progress and supporting patient management.

    关键字:Biomedical informatics; Data science; Data ecosystem

  • IT in Biology & Medical Informatics: On the Challenge of Understanding the Data Ecosystem

    Andreas Holzinger;Miroslav Bursa;Sami Khuri;M. Elena Renda;

    International conference on information technology in bio- and medical informatics

    2017年

  • A Hybrid Feature Selection Method to Classification and Its Application in Hypertension Diagnosis

    作者:Hyun Woo Park;Dingkun Li;Yongjun Piao;Keun Ho Ryu; 会议名称:International conference on information technology in bio- and medical informatics 2017年

    Recently, various studies have shown that meaningful knowledge can be discovered by applying data mining techniques in medical applications, i.e., decision support systems for disease diagnosis. However, there are still several computational challenges due to the high-dimensionality of medical data. Feature selection is an essential pre-processing procedure in data mining to identify relevant feature subset for classification. In this study, we proposed a hybrid feature selection mechanism by combining symmetrical uncertainty and Bayesian network. As a case study, we applied our proposed method to the hypertension diagnosis problem. The results showed that our method can improve the classification performance and outperformed existing feature selection techniques.

    关键字:Classification; Feature selection; Hypertension; KNHANES; Data mining

  • A Hybrid Feature Selection Method to Classification and Its Application in Hypertension Diagnosis

    Hyun Woo Park;Dingkun Li;Yongjun Piao;Keun Ho Ryu;

    International conference on information technology in bio- and medical informatics

    2017年

  • Modelling of Cancer Patient Records: A Structured Approach to Data Mining and Visual Analytics

    作者:Jing Lu;Alan Hales;David Rew; 会议名称:International conference on information technology in bio- and medical informatics 2017年

    This research presents a methodology for health data analytics through a case study for modelling cancer patient records. Timeline-structured clinical data systems represent a new approach to the understanding of the relationship between clinical activity, disease pathologies and health outcomes. The novel Southampton Breast Cancer Data System contains episode and timeline-structured records on > 17,000 patients who have been treated in University Hospital Southampton and affiliated hospitals since the late 1970s. The system is under continuous development and validation. Modern data mining software and visual analytics tools permit new insights into temporally-structured clinical data. The challenges and outcomes of the application of such software-based systems to this complex data environment are reported here. The core data was anonymised and put through a series of pre-processing exercises to identify and exclude anomalous and erroneous data, before restructuring within a remote data warehouse. A range of approaches was tested on the resulting dataset including multidimensional modelling, sequential patterns mining and classification. Visual analytics software has enabled the comparison of survival times and surgical treatments. The systems tested proved to be powerful in identifying episode sequencing patterns which were consistent with real-world clinical outcomes. It is concluded that, subject to further refinement and selection, modern data mining techniques can be applied to large and heterogeneous clinical datasets to inform decision making.

    关键字:Clinical data environment; Electronic patient records; Health information systems; Data mining; Visual analytics; Decision support

  • Modelling of Cancer Patient Records: A Structured Approach to Data Mining and Visual Analytics

    Jing Lu;Alan Hales;David Rew;

    International conference on information technology in bio- and medical informatics

    2017年

  • A Review of Model Prediction in Diabetes and of Designing Glucose Regulators Based on Model Predictive Control for the Artificial Pancreas

    作者:Kyriaki Saiti;Martin Macas;Katerina Stechova;Pavlina Pithova;Lenka Lhotska; 会议名称:International conference on information technology in bio- and medical informatics 2017年

    The present work presents a comparative assessment of glucose prediction models for diabetic patients using data from sensors monitoring blood glucose concentration as well as data from in silico simulations. The models are based on neural networks and linear and nonlinear mathematical models evaluated for prediction horizons ranging from 5 to 120 min. Furthermore, the implementation of compartment models for simulation of absorption and elimination of insulin, caloric: intake and information about physical activity is examined in combination with neural networks and mathematical models, respectively. This assessment also addresses the recent progress and challenges in designing glucose regulators based on model predictive control used as part of artificial pancreas devices for type 1 diabetic patients. The assessments include 24 papers in total, from 2006 to 2016, in order to investigate progress in blood glucose concentration prediction and in Artificial Pancreas devices for type 1 diabetic patients.

    关键字:Prediction; Diabetes; Model predictive control; Artificial pancreas

  • A Review of Model Prediction in Diabetes and of Designing Glucose Regulators Based on Model Predictive Control for the Artificial Pancreas

    Kyriaki Saiti;Martin Macas;Katerina Stechova;Pavlina Pithova;Lenka Lhotska;

    International conference on information technology in bio- and medical informatics

    2017年

  • Riemannian Geometry in Sleep Stage Classification

    作者:Elizaveta Saifutdinova;Vaclav Gerla;Lenka Lhotska; 会议名称:International conference on information technology in bio- and medical informatics 2017年

    The study is devoted to the, sleep stage identification problem. Proposed method is based on calculation of covariance matrices from segments of multi-modal recordings. Mathematical properties of the extracted covariance matrices allow to define a distance between two segments - a distance in a Riemannian manifold. In the paper we tested minimum distance to a class center and k-nearest-neighbours classifiers with the Riemannian metric as a distance between two objects, and classification in a tangent space to a Riemannian manifold. Methods were tested on the data of patients suffering from sleep disorders. The maximum obtained accuracy for KNN is 0.94, for minimum distance to a class center it is only 0.816 and for classification in a tangent space is 0.941.

    关键字:Sleep EEC; Sleep stages; Riemannian geometry; Classification

  • Riemannian Geometry in Sleep Stage Classification

    Elizaveta Saifutdinova;Vaclav Gerla;Lenka Lhotska;

    International conference on information technology in bio- and medical informatics

    2017年

  • Reducing Red Blood Cell Transfusions

    作者:James P. McGlothlin;Evan Crawford;Hari Srinivasan;Carissa Cianci;Brenda Bruneau;Ihab Dorotta; 会议名称:International conference on information technology in bio- and medical informatics 2017年

    The health care industry in the United States is undergoing a paradigm shift from the traditional fee-for-service model to various payment and incentive models based on quality of care rather than quantity of services. One specific scenario where more treatment does not equate to better care is red blood cell transfusions. While blood transfusions often save lives, there arc numerous complications which can result and blood should be transfused only if medically necessary. Several studies have indicated that a very high percentage of units transfused are not clinically appropriate. These transfusions increase cost and negatively impact patient outcomes. In this paper, we will present an analytics project to identify and track the transfusions which are performed without clear necessity. Furthermore, we will describe how we utilized data discovery and supervised learning to improve our classification algorithm and the accuracy of our results. We will demonstrate that our project is effectively reducing red blood cell transfusions.

    关键字:Healthcare analytics; Data warehouses; Blood utilization; Quality

  • Reducing Red Blood Cell Transfusions

    James P. McGlothlin;Evan Crawford;Hari Srinivasan;Carissa Cianci;Brenda Bruneau;Ihab Dorotta;

    International conference on information technology in bio- and medical informatics

    2017年

  • Statistical Analysis of Perinatal Risk Factors for Emergency Caesarean Section

    作者:Ibrahim Abou Khashabh;Vaclav Chudacek;Michal Huptych; 会议名称:International conference on information technology in bio- and medical informatics 2017年

    Objective: To explore potential risk factors for the emergency caesarean section in term, singleton pregnancies. Methods: A retrospective population based case-control study in term deliveries from the University Hospital in Brno, Czech Republic collected between 2014 and 2016. Cases were deliveries by emergency caesarean section; controls were all others modes of delivery. We excluded elective caesarean from the populations. Results: In the database of 13769 deliveries, we identified 2178 cases. Univariate and multivariable analysis of clinical features were performed. The following risk factors were associated with emergency caesarean section: Breech presentation OR 21.6 (14.6 30.5), obstructed labor OR 42.7 (28.5-63.9), scar on uterus OR 18 (14.3-22.5), fetal distress OR 6.1 (5.3-7.2) and primipara OR 3.7 (3.1-4.4). Conclusion: Univariate and multivariable analysis of the data from 13769 deliveries were performed, and significant risk factors were identified increasing the chance of undergoing caesarean section.

    关键字:

  • Statistical Analysis of Perinatal Risk Factors for Emergency Caesarean Section

    Ibrahim Abou Khashabh;Vaclav Chudacek;Michal Huptych;

    International conference on information technology in bio- and medical informatics

    2017年

  • Contextual Decision Making for Cancer Diagnosis

    作者:Samia Sbissi;Said Gattoufi; 会议名称:International conference on information technology in bio- and medical informatics 2017年

    Pathologist needs to routinely make management decisions about patients who are at risk for a disease such as cancer. Although, making a decision for cancer diagnosis is a dificult task since it context dependent. The term context contains a large number of elements that limits strongly any possibility to automatize this. The decision-making the process being highly contextual, the decision support system must benefit from its interaction with the expert to learn new practices by acquiring missing knowledge incrementally and learning new practices, it is called in deferent research human/doctor in the loop, and thus enriching its experience base.

    关键字:Decision making; Decision support system; Cancer diagnosis

  • Contextual Decision Making for Cancer Diagnosis

    Samia Sbissi;Said Gattoufi;

    International conference on information technology in bio- and medical informatics

    2017年

  • Audit Trails in OpenSLEX: Paving the Road for Process Mining in Healthcare

    作者:Eduardo Gonzalez Lopez dc Murillas;Emmanuel Helm;Hajo A. Reijers;Josef Kueng; 会议名称:International conference on information technology in bio- and medical informatics 2017年

    The analysis of organizational and medical treatment processes is crucial for the future development of the healthcare domain. Recent approaches to enable process mining on healthcare data make use of the hospital information systems' Audit Trails. In this work, methods are proposed to integrate Audit Trail data into the generic OpenSLEX meta model to allow for an analysis of healthcare data from different perspectives (e.g. patients, doctors, resources). Instead of flattening the event data in a single log file the proposed methodology preserves as much information as possible in the first stages of data extraction and preparation. By building on established standardized data and message specifications for auditing in healthcare, we increase the range of analysis opportunities in the healthcare domain.

    关键字:Process mining; Healthcare; Audit trails; Meta model

  • Audit Trails in OpenSLEX: Paving the Road for Process Mining in Healthcare

    Eduardo Gonzalez Lopez dc Murillas;Emmanuel Helm;Hajo A. Reijers;Josef Kueng;

    International conference on information technology in bio- and medical informatics

    2017年

  • The Use of Convolutional Neural Networks in Biomedical Data Processing

    作者:Miroslav Bursa;Lenka Lhotska; 会议名称:International conference on information technology in bio- and medical informatics 2017年

    In this work, we study the use of convolutional neural networks for biomedical signal processing. Convolutional neural networks show promising results for classifying images when compared to traditional multilayer perceptron, as the latter do not. take spatial structure of the data into an account. Cardiotocography (CTG) is a monitoring of fetal heart rate (FHR) and uterine contractions (UC) used by obstetricians to assess fetal well-being. Because of the complexity of FHR dynamics, regulated by several neurological feedback loops, the visual inspection of FHR remains a difficult task. The application of most guidelines often result in significant inter-and intra-observer variability. Convolutional neural network (CNN, or ConvNet) is inspired by the organization of the animal visual cortex. In the paper we are applying continuous wavelet transform (CWT) to the UC and FHR signals with different levels of time/frequency detail parameter and in two different resolutions. The output 2D structures are fed to convolutional neural network (we are using Tensorflow framework) and we are minimizing the cross entropy function. On the testing dataset (with pH threshold at 7.15) we have achieved the accuracy of 94.1% which is a promising result that needs to be further studied.

    关键字:Data mining; Cardiotocography; Intrapartum; Signal processing; Convolutional neural networks

  • The Use of Convolutional Neural Networks in Biomedical Data Processing

    Miroslav Bursa;Lenka Lhotska;

    International conference on information technology in bio- and medical informatics

    2017年

  • Preface

    作者:M. Elena Renda;Miroslav Bursa;Andreas Holzinger;Sami Khuri; 会议名称:International conference on information technology in bio- and medical informatics 2017年

    Biomedical engineering and medical informatics represent challenging and rapidly growing areas. Applications of information technology in these areas are of paramount importance. Building on the success of ITBAM 2010, ITBAM 2011, ITBAM 2012, ITBAM 2013, ITBAM 2014, ITBAM 2015, and ITBAM 2016, the aim of the 8th International Conference on Information Technology in Bio- and Medical Informatics (ITBAM) conference was to continue bringing together scientists, researchers, and practitioners from different disciplines, namely, from mathematics, computer science, bioinformatics, biomedical engineering, medicine, biology, and different fields of life sciences, to present and discuss their research results in bioinformatics and medical informatics.

    关键字:

  • Preface

    M. Elena Renda;Miroslav Bursa;Andreas Holzinger;Sami Khuri;

    International conference on information technology in bio- and medical informatics

    2017年

  • What Do the Data Say in 10 Years of Pneumonia Victims? A Geo-Spatial Data Analytics Perspective

    作者:Maribel Yasmina Santos;Antonio Carvalheira Santos;Artur Teles de Araujo; 会议名称:International conference on information technology in bio- and medical informatics 2016年

    The need to integrate, store, process and analyse data is continuously growing as information technologies facilitate the collection of vast amounts of data. These data can be in different repositories, have different data formats and present data quality issues, requiring the adoption of appropriate strategies for data cleaning, integration and storage. After that, suitable data analytics and visualization mechanisms can be used for the analysis of the available data and for the identification of relevant knowledge that support the decision-making process. This paper presents a data analytics perspective over 10 years of pneumonia incidence in Portugal, pointing the evolution and characterization of the mortal victims of this disease. The available data about the individuals was complemented with statistical data of the country, in order to characterize the overall incidence of this disease, following a spatial analysis and visualization perspective that is supported by several analytical dashboards.

    关键字:Business intelligence; (Spatial) data warehouse; Data analytics; Pneumonia

  • What Do the Data Say in 10 Years of Pneumonia Victims? A Geo-Spatial Data Analytics Perspective

    Maribel Yasmina Santos;Antonio Carvalheira Santos;Artur Teles de Araujo;

    International conference on information technology in bio- and medical informatics

    2016年

  • Ontology-Guided Principal Component Analysis: Reaching the Limits of the Doctor-in-the-Loop

    作者:Sandra Wartner;Dominic Girardi;Manuela Wiesinger-Widi;Johannes Trenkler;Raimund Kleiser;Andreas Holzinger; 会议名称:International conference on information technology in bio- and medical informatics 2016年

    Biomedical research requires deep domain expertise to perform analyses of complex data sets, assisted by mathematical expertise provided by data scientists who design and develop sophisticated methods and tools. Such methods and tools not only require preprocessing of the data, but most of all a meaningful input selection. Usually, data scientists do not have sufficient background knowledge about the origin of the data and the biomedical problems to be solved, consequently a doctor-in-the-loop can be of great help here. In this paper we revise the viability of integrating an analysis guided visualization component in an ontology-guided data infrastructure, exemplified by the principal component analysis. We evaluated this approach by examining the potential for intelligent support of medical experts on the case of cerebral aneurysms research.

    关键字:Principal component analysis; Ontology; Data mining; PCA; Data warehousing; Doctor-in-the-loop

  • Ontology-Guided Principal Component Analysis: Reaching the Limits of the Doctor-in-the-Loop

    Sandra Wartner;Dominic Girardi;Manuela Wiesinger-Widi;Johannes Trenkler;Raimund Kleiser;Andreas Holzinger;

    International conference on information technology in bio- and medical informatics

    2016年

  • Integrating Open Data on Cancer in Support to Tumor Growth Analysis

    作者:Fleur Jeanquartier;Claire Jean-Quartier;Tobias Schreck;David Cemernek;Andreas Holzinger; 会议名称:International conference on information technology in bio- and medical informatics 2016年

    The general disease group of malignant neoplasms depicts one of the leading and increasing causes for death. The underlying complexity of cancer demands for abstractions to disclose an exclusive subset of information related to the disease. Our idea is to create a user interface for linking a simulation on cancer modeling to relevant additional publicly and freely available data. We are not only providing a categorized list of open datasets and queryable databases for the different types of cancer and related information, we also identify a certain subset of temporal and spatial data related to tumor growth. Furthermore, we describe the integration possibilities into a simulation tool on tumor growth that incorporates the tumor's kinetics.

    关键字:Open data; Data integration; Cancer; Tumor growth; Data; Visualization; Simulation

  • Integrating Open Data on Cancer in Support to Tumor Growth Analysis

    Fleur Jeanquartier;Claire Jean-Quartier;Tobias Schreck;David Cemernek;Andreas Holzinger;

    International conference on information technology in bio- and medical informatics

    2016年

  • Adaptive Segmentation Optimization for Sleep Spindle Detector

    作者:Elizaveta Saifutdinova;Martin Macas;Vaclav Gerla;Lenka Lhotska; 会议名称:International conference on information technology in bio- and medical informatics 2016年

    Segmentation is a crucial part of the signal processing as it has a significant influence on further analysis quality. Adaptive segmentation based on sliding windows is relatively simple, works quite good and can work online. It has however many tunable parameters whose proper values depend on the task and signal type. The paper proposes a method of defining optimal parameters for detection of sleep spindles in electroencephalogram. Segmentation algorithm based on Varri method was utilized. Fitness function was proposed for estimation of agreement between the segmentation result and borders of the target classification. Particle swarm optimization was used to find optimal parameters. On the data of 11 insomniac subjects the method reached 28 % improvement in comparison to the baseline method using default parameters.

    关键字:Sleep EEG; Adaptive segmentation; Optimization; Sleep spindles; Particle swarm optimization

  • Adaptive Segmentation Optimization for Sleep Spindle Detector

    Elizaveta Saifutdinova;Martin Macas;Vaclav Gerla;Lenka Lhotska;

    International conference on information technology in bio- and medical informatics

    2016年

  • Multidisciplinary Team Meetings - A Literature Based Process Analysis

    作者:Oliver Krauss;Martina Angermaier;Emmanuel Helm; 会议名称:International conference on information technology in bio- and medical informatics 2016年

    Multidisciplinary Team Meetings (MDTM) are conducted to discuss the treatment of one or more patients. This paper discusses MDTM with a focus on tumor treatment and shows workflows in different settings, identifies organizational and technical problems in the MDTM and solutions thereof. It aims to answer the following research questions: (RQ1) What is the current state of the art in MDTM?(RQ2) How are they conducted and what is the variation in different hospital settings? (RQ3) What technical problems and possible solutions thereof exist? This is done by conducting a literature review entailing a forward search of 837 papers and a backward search. The results show that a unified workflow model for MDTM can't be found since they are highly dependent on institutional and tumor dependent specifics. The identified problems and solutions show a lack of research towards technical solutions and process interoperability. An outlook on extending research in these areas is given.

    关键字:Tumor board; Multidisciplinary team meeting; Workflow; Process analysis

  • Multidisciplinary Team Meetings - A Literature Based Process Analysis

    Oliver Krauss;Martina Angermaier;Emmanuel Helm;

    International conference on information technology in bio- and medical informatics

    2016年

  • A Clinical Case Simulation Tool for Medical Education

    作者:Juliano S. Gaspar;Marcelo R. Santos Jr.;Zilma S.N. Reis; 会议名称:International conference on information technology in bio- and medical informatics 2016年

    The human being, even if potentially inclined to learn, needs incentives to do it effectively. In these context, the virtual environments could simulate challenges of clinical practice and, at the same time, consider the personal experiences, allows the student's stimulus and also offer additional theoretical content updated and of excellent quality. The purpose of the project is to develop a Clinical Case Simulation Tool (CCST), it's supposed to be a supporter to the acquisition of clinical skills for medical education. This is an experimental study of applied technology for health education. The project is multidisciplinary between health sciences, computing and education. The development of an application to store real clinical cases is the starting point of this study. The structure of the proposed clinical case comprises the description of the case, clinical history, complementary tests, questions and further reading. The access to the application is password protected, composed of access profiles with specific characteristics such as teacher, coordinator, student. All clinical cases are linked to a specific college and discipline. The Clinical Cases simulator platform was created for storage of clinical cases and to provide technological support for preparing courses, workshops and support classroom teaching. This may be considered as an innovative approach, given the use of a digital system that enables the storage of clinical data and laboratory tests, as sounds of cardiac auscultation, pulmonary auscultation, images and videos.

    关键字:Computer simulation; Gamification; Competency-Based education; Clinical diagnosis; Medical education

  • A Clinical Case Simulation Tool for Medical Education

    Juliano S. Gaspar;Marcelo R. Santos Jr.;Zilma S.N. Reis;

    International conference on information technology in bio- and medical informatics

    2016年

  • Importance and Quality of Eating Related Photos in Diabetics

    作者:Kyriaki Saiti;Martin Macas;Lenka Lhotska; 会议名称:International conference on information technology in bio- and medical informatics 2016年

    Data are the crucial component of most computer based clinical decision support systems. This review focuses on data for a system which should improve everyday life of diabetics. The aim is to identify issues arising during the process of acquisition of photos of dishes obtained by diabetic patients. Solutions are proposed that will improve the quality of subsequent processing and final conclusions. This research will lead to a proposal of some guidelines that patients should follow when taking the pictures of dishes. For this purpose, a sample of 906 photos from 6 patients including meals and text records of activities was examined carefully in order to extract useful information about how do diabetics chose to record the details, how much and how long do they follow the suggestions. Based on the analysis, representative examples are presented with corresponding suggestions for each case.

    关键字:Data analysis; Data quality; Food; Diabetes; Photos; Meals

  • Importance and Quality of Eating Related Photos in Diabetics

    Kyriaki Saiti;Martin Macas;Lenka Lhotska;

    International conference on information technology in bio- and medical informatics

    2016年

  • Applying Ant-Inspired Methods in Childbirth Asphyxia Prediction

    作者:Miroslav Bursa;Lenka Lhotska; 会议名称:International conference on information technology in bio- and medical informatics 2016年

    In the today's world we witness an impact of the 'Big data' phenomenon. Although there are many definitions and different scientists view the problem from their perspectives (web, IoT, smartphones, security, GIS, HIS, cloud systems, networks,...), there is still need for efficient, robust and scalable algorithms that ease processing of such data. This paper deals with data that might not fit into the Big data definitions, however the amount of the work needed even for such smaller data-mining problem, is enormous. The main reason is the heterogeneity of the data, multiple variants and synonyms in the terminology used, natural language processing caveats and many errors, omissions and typos (spelling errors).

    关键字:Data mining; Textual data processing; Data visualization; Ant colony optimization; Hospital information system; Decision tree induction

  • Applying Ant-Inspired Methods in Childbirth Asphyxia Prediction

    Miroslav Bursa;Lenka Lhotska;

    International conference on information technology in bio- and medical informatics

    2016年

  • Integrated DB for Bioinformatics: A Case Study on Analysis of Functional Effect of MiRNA SNPs in Cancer

    作者:Antonino Fiannaca;Laura La Paglia;Massimo La Rosa;Antonio Messina;Pietro Storniolo;Alfonso Urso; 会议名称:International conference on information technology in bio- and medical informatics 2016年

    The era of "big data" arose the need to have computational tools in support of biological tasks. Many types of bioinformatics tools have been developed for different biological tasks as target, pathway and gene set analysis, but integrated resources able to incorporate a unique web interface, and to manage a biological scenario involving many different data sources are still lacking. In many bioinformatics approaches several data processing and evaluation steps are required to reach the final results. In this work, we face a biological case study by exploiting the capabilities of an integrated multi-component resources database that is able to deal with complex biological scenarios. As example of our problem-solving approach we provide a case study on the analysis of functional effect of miRNA single nucleotide polymorphisms (SNPs) in cancer disease.

    关键字:Integrated databases; miRNA SNP; BioGraphDB; miRNA-target interactions

  • Integrated DB for Bioinformatics: A Case Study on Analysis of Functional Effect of MiRNA SNPs in Cancer

    Antonino Fiannaca;Laura La Paglia;Massimo La Rosa;Antonio Messina;Pietro Storniolo;Alfonso Urso;

    International conference on information technology in bio- and medical informatics

    2016年

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6.其他规定

(1)本协议内容受中华人民共和国法律的约束。如果本协议中任何规定被裁定为无效或不可强制执行,该项规定应被撤销,而其余规定继续有效。

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注意:六维联合未就您或其他人士的某项违约行为采取行动,并不表明六维联合就任何继后或类似的违约事件放弃采取行动的权利。


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