Data Mining calls for papers / publications

Call for Papers for a Special Issue of the International Journal of Nano and Biomaterials: Machine Learning and Pattern Recognition in Bioinformatics

Guest Editors:
Prof. Feng Liu and Prof. Wen Zhang, Wuhan University, China

Currently, a great amount of data are being generated which range from gene expression and micro RNA array data through to next generation sequence data. Data interpretation draws on mathematical and computational skills and thus the subject has engaged the interest of researchers in areas such mathematics, bioinformatics and computer science.

This cross-disciplinary special issue aims to bring together top researchers, practitioners and students from all over the world to explore and present innovative machine learning and pattern recognition approaches to solve realistic problems in bioinformatics and biomedicine.

Subject Coverage

Suitable topics include but are not limited to:

Microarray gene expression data analysis
Protein structure and function prediction
Molecular interaction and regulation network inference
Immunoinformatics and cheminformatics
High throughput sequencing data analysis
Text mining in biomedical literatures
Algorithms in molecular modelling
Biological databases, integration and visualisation
New machine learning methods for bioinformatics
Genome-wide association studies
Biomarker discovery
Gene network analysis
Tools and algorithms in bioinformatics
Other related topics  

Notes for Prospective Authors

Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper was not originally copyrighted and if it has been completely re-written).

All papers are refereed through a peer review process. A guide for authors, sample copies and other relevant information for submitting papers are available on the Author Guidelines page http://www.inderscience.com/mapper.php?id=31

Important Dates

Full paper deadline: 25 July, 2012

Acceptance notification: 15 September, 2012

Final revised submission: 10 October, 2012

All papers must be submitted online.

Call for Papers for a Special Issue of the Semantic Web Journal: Big Data and the Semantic Web

The Semantic Web journal calls for innovative and high-quality papers describing the role of Semantic Web technologies, Linked Data, and ontologies for the Big Data age. Papers should clearly relate to one or more of the Big Data V's Volume, Variety, and Velocity, as well as demonstrate the added value of semantics. Besides theoretical contributions on reasoning over massive amounts of heterogeneous data and challenges for knowledge representation and interlinkage, we especially also invite reports from domain scientists detailing the use of ontologies and Semantic Web technologies in bioinformatics, geographic information science, life sciences, cultural heritage research, the digital humanities, and other research areas.

We welcome all paper categories, i.e., full research papers, application reports, systems and tools, ontology papers, surveys, as well as dataset reports as long as they clearly relate to challenges and opportunities arising from processing Big Data - see our listing of paper types in the author guidelines http://www.semantic-web-journal.net/authors

Topics include but are not limited to

Semantic search and information seeking
Exploratory interfaces for massive amounts of annotated data
Intelligent information interchange
Semantic interoperability and heterogeneity
Inductive and abductive approaches to ontology learning
Handling uncertainty, vagueness, and inconsistencies
Knowledge discovery from linked data
Collaborative Ontology engineering
Microtheories and knowledge patterns
Ontology modularization
Ontology evolution
Ontology alignment, matching, and translation
Analogy and similarity reasoning and retrieval
Sensor semantics and smart dust
Stream reasoning
Distributed reasoning
Semantics-based data aggregation and generalization
Semantically enabled statistics
Massive data integration for the digital earth
Linked science
The User as knowledge engineer
Semantics and decision support systems
Semantics-driven integrity constraint checking
Mining the Social and Mobile Web
Ontology-driven data visualization
Trust and privacy issues in publishing and reasoning about Big Data
Dialog and question answering systems based on Linked Data and ontologies

Important Dates
Manuscript submission due: 30th of June 2012
First notification: 7th of September 2012
Issue publication: Spring 2013

Submissions
The special issue on Big Data and the Semantic Web calls for original high-quality research on any of the above mentioned topics. Authors are requested to follow the author guidelines, submit online as detailed in the author guidelines, and include the name of the call within the submission letter. All manuscripts will be reviewed based on the SWJ open and transparent review policy and will be made available during online the review process.

Call for Papers for a Special Issue of Artificial Intelligence in Medicine: Medical Data Streams

An Elsevier Journal

Many artificial intelligence researchers coming from different areas (data mining, machine learning, intelligent data analysis, pattern recognition, fuzzy logic, databases, etc.) design new approaches or adapt some of the traditional algorithms to data streams. In many medical applications different domain experts, e.g. physicians (would) benefit from the integration of the streaming medical data into decision support systems.

The goal of this special issue is to gather researchers who deal with artificial intelligence for data processing, data management and knowledge discovery in clinical scenarios where data is produced as a continuous stream.

IMPORTANT DATES

Submission deadline: 18 Jun 2012 *
Review notification: 18 Sept 2012
Revised submission: 18 Nov 2012
Second notification: 18 Dec 2012
Camera-ready submission: 18 Jan 2013

* earlier submissions are welcome; review process will start immediately after submission

RATIONALE

Artificial Intelligence in Medicine is facing a new challenge, created by the rapid growth in information science and technology in general and the complexity and volume of data in particular. Medical settings are using sensors and networks of health information systems to integrate data from patients, which requires storage, processing and management operators to enable further analysis and knowledge discovery. The main issue is that this data production often takes the form of high-speed continuous flows of data.

Medical domains include several settings where data is produced in a streaming fashion, such as anatomical and physiological sensors, or incidence records and health information systems. New services appear allowing users to store and track information about their medical history, to connect to and stream data from medical devices. Medical data streams have become widespread and call for development of intelligent tools for making use of these data. Decision support, alerting services, ambient intelligence, assisted leaving and personalization services are just few examples of expected uses of actionable knowledge extracted from medical data streams. All of them are characterized by the high-speed at which huge amounts of data are produced, and often require fast and accurate information retrieval and analysis, that can effectively support clinical decisions.

Dealing with continuous, and possibly infinite, flows of data require different approaches for data processing and management, and further machine learning and knowledge discovery. Particular issues to address include summarization of infinite data, incremental and decremental learning, resource-awareness, real-time monitoring of changes and recurrences, etc. This is an incremental task that requires incremental algorithms that integrate very large data bases in medical domains. Streaming artificial intelligence is increasingly important in the research community, as new algorithms are needed to process medical data in reasonable time.

Furthermore, medical domains introduce extra peculiarities to the problem. For example, health information systems now deal with heterogeneous data sources, possibly distributed across health-care institutions. Moreover, this data integration requirement yields privacy-preserving issues. At the same time, it forces the system to take time, resources, and costs into consideration. Currently, generic techniques for intelligent analysis and learning from streaming data include also processing and management techniques which are widely spread in the applied computing research community. Also, in the medical domain, technological issues of data collection and storage, access, integration, information fusion, etc are also widely studied in the health informatics research community. However, adoption and development of tailored techniques for medical stream mining and clinical decision support is still to come.

The goal of this special issue is to present cutting-edge research from experts in data stream processing interested in medical applications and medical domain experts interested in timely analysis of their data streams for clinical decision support.

TOPICS

Topics include but are not restricted to processing, managing and knowledge discovery for:
Anatomical or physiological sensor data streams
Data streams in health-care
Integrating biomedical signals and electronic health records
Integrated health information data streams
Adaptive health information systems
Medical data stream models
Mobile and ubiquitous medical data streams
Data quality in medical data streams
Data streams integration in intensive care units
Remote monitoring of patients in hospital and ambulatory settings
Process mining from medical data streams
Case reports of medical scenarios where data is produced in a stream
Real-time and real-world applications using streaming medical data
Languages and ontologies for medical stream query
Integration with real-time enactment of clinical guidelines
Privacy and security issues in medical data streams

SPECIAL ISSUE GUEST EDITORS

Pedro Pereira Rodrigues - LIAAD & Faculty of Medicine, University of Porto, Portugal
Mykola Pechenizkiy - Eindhoven University of Technology, the Netherlands
Mohamed Medhat Gaber - University of Portsmouth, United Kingdom
Carolyn McGregor - University of Ontario Institute of Technology, Canada
João Gama - LIAAd & Faculty of Economics, University of Porto, Portugal

PAPER FORMATTING, SUBMISSION AND REVIEWING

Authors should follow the guide to authors available at AIIM website to format their article. Please note that, for the initial submission, only PDF format of submissions is allowed. Papers to this special issue should be submitted by email to the guest editors at pprodrigues@med.up.pt and not via the online Elsevier Editorial System.

Each paper submission will be peer-reviewed by at least three reviewers. The quest editors will screen the submissions for eligibility and quality. Special issue articles should report on significant previously unpublished work.

We do invite authors to submit their revised and substantially extended workshop and conference papers. As a rule of thumb the journal paper submission should contain at least 30% of new previously unpublished material. Please indicate in your cover letter whether the journal paper submission is based on or extend substantially a previously published conference or workshop paper, in case of which a description of what is new must be clarified in the submission.

All papers accepted to the special issue are subject to the final approval by the Editor-in-Chief of AIIM journal. It is planned that the articles will appear in one of the issues of the Artificial Intelligence in Medicine Journal, edited and published by Elsevier, in 2013. AIIM typically has 9 issues per year.

Call for Papers for Special Issue or Section of the Journal of Consulting and Clinical Psychology: Advances in Data Analytic Methods for Evaluating Treatment Outcome and Mechanisms of Change

Important Dates

June 1, 2012: deadline to submit a 1-page proposal outlining the full manuscript
July 1, 2012: notification to authors of selected proposals
October 1, 2012: deadline to submit full manuscript

The Journal of Consulting and Clinical Psychology (JCCP) plans to publish a special issue or section on "Advances in Data Analytic Methods for Evaluating Treatment Outcome and Mechanisms of Change" in 2013.

Over the past decade, there has been considerable advancement in the areas of data and statistical modeling to better test hypotheses about treatment trajectory, outcomes, moderation, mediation, and the appropriate handling of missing data.

The objective of this special issue is to facilitate the dissemination of these new technologies, thereby enhancing the quality of research as it relates to topics central to JCCP.

To this end, we are calling for original manuscript submissions within this broad framework, which include, but are not limited to, the following topics:

Applying sophisticated growth curve models to more accurately model change in outcomes over time;
Multivariate multilevel modeling;
Appropriate management of missing data;
Addressing non ignorable missingness;
Multilevel meta-analyses;
Examining predictors and moderators of treatment outcome;
Establishing causal inference

We intend to publish papers that introduce recent developments in data analysis and illustrate their utility for advancing knowledge about treatment efficacy and mechanisms of change, using clinically relevant examples.

Ideal manuscripts would preferably demonstrate the application of the technique(s) to an existing dataset or to simulated datasets (as in a Monte Carlo study), possibly with a comparison to other available and often employed techniques.

As such, the papers in this special issue/section can complement articles covering these topics published in other established outlets (e.g., Psychological Methods, Statistics in Medicine), which typically provide a more technical analysis of the statistical performance of various techniques and approaches.

The editors for this issue are David Rosenfield (Guest Editor), Scott N. Compton (JCCP Associate Editor), Stefan G. Hofmann (JCCP Associate Editor) and Jasper A. J. Smits (JCCP Incoming Associate Editor).

Authors interested in having a manuscript considered for this special issue/section need to first submit a 1-page proposal outlining the full manuscript by June 1, 2012. Authors of selected proposals will be notified by July 1, 2012 inviting them to submit a full paper due October 1, 2012.

All invited manuscripts will undergo the normal peer review process. Note that an initial invitation does not guarantee acceptance. All manuscripts should be prepared in strict accordance with JCCP guidelines (see the Instructions to Authors section of the JCCP homepage) and eventually submitted through the JCCP manuscript submission portal.

Questions about appropriate topics, as well as the 1-page proposals, can be sent to Dr. David Rosenfield.