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Wednesday, April 4, 2018

AI100: 2018 Call for Participation

The Stanford One Hundred Year Study on Artificial Intelligence, AI100, launched in Fall 2014, is an endowed, long-range investigation of Artificial Intelligence (AI). It examines AI systems and the technological, ethical, and policy opportunities and dilemmas that they present to individuals, communities, and society. The AI100 Standing Committee (AI100SC) oversees the Study's core activity: Designing and carrying out, on a five-year cycle, studies that assess the current state and future potential of AI-enabled computing systems. Resulting Study Panel Reports aim to inform and prompt action from diverse stakeholders as they navigate the promise and challenges that AI advancements raise for how people work, live, and play.

AI100's first study, "AI and Life in 2030", was issued in 2015-16. The AI100SC, in preparation for its next study cycle, is pleased to issue this call for proposals to convene multidisciplinary communities of scholars and stakeholders. The AI100SC will select and host two focused studies – carried out through interactive study-workshops – over the next two years, providing $15,000 to each winning proposal. AI100SC may also choose to fund a third study-workshop. Results from these study-workshops will form the substance of the 2020 AI100 Report. The AI100SC invites applications on topics and issues core to its mission that bring together an international community of AI researchers and practitioners with a broad representation of fields relevant to AI's impact in the world. The AI100SC is particularly interested in spurring conversations that connect and build on the expertise of computer scientists and engineers; scholars in the humanities, including historians and philo sophers of ethics, science and technology; the social sciences, including anthropologists, economists, media scholars, psychologists, and sociologists; law and public policy experts; and representatives from business management as well as the private and public sectors.

Initial proposals for study-workshops, due April 23, 2018, should take the form of an abstract no longer than 500 words that briefly describes the questions to be studied, the rationale for the study-workshops, the intended range of disciplinary expertise and participation, a general plan for carrying out the study-workshop, and intended format for communicating study-workshop results. AI100 will provide financial support and organizational assistance for each study-workshop as well as resources to disseminate the workshop's study results. Details about workshop scheduling, budget, review timelines, and criteria for evaluating proposals will be maintained at: https://ai100.stanford.edu/workshop

We look forward to hosting a lively and informative set of studies that will produce new ideas and enrich our understanding of AI and its influence on people and society.

Learn more and submit a proposal: https://ai100.stanford.edu/workshop.



What are the important dates that I should track?

April 23, 2018, 5pm PT: initial 500-word abstracts due
June 1, 2018: ten finalists receive notice requesting a full proposal
June 29, 2018, 5pm PT: 2,500-word full proposal due
August 17, 2018: all finalists notified of their proposal status
Early Fall, 2018: Public announcement of the study-workshops selected
URL: https://ai100.stanford.edu/workshop

Contact Person: Jacqueline Tran (ai100-info@lists.stanford.edu)

Saturday, February 10, 2018

Call for Special Session Proposals: 15th Computational Intelligence methods for Bioinformatics and Biostatistics

CIBB 2018 : 15th Computational Intelligence methods for Bioinformatics and Biostatistics

Caparica, Portugal, September 6-8, 2018

http://eventos.fct.unl.pt/cibb2018/


Call for Papers, Tutorials and Special Sessions

The main goal of the CIBB international conference is to provide a multi-disciplinary forum for researchers interested in the application of computational intelligence, in a broad sense, to open problems in bioinformatics, biostatistics, systems and synthetic biology and medical informatics. Cutting edge methodologies capable of accelerating life science discoveries will be discussed.

Following its tradition and roots, this year's meeting will bring together researchers from the international scientific community interested in advancements and future perspectives in bioinformatics and biostatistics. Also of particular interest are current trends and future opportunities at the edge of computer and life sciences, together with the application of computational intelligence to system and synthetic biology, and the consequent impact on innovative medicine. Theoretical and experimental biologists are invited to participate in order to present novel challenges and foster multidisciplinary collaboration.

The scientific program of CIBB 2018 will include Keynote Speakers, tutorials and special sessions. Contributed papers will be presented in plenary oral sessions, special sessions, or poster sessions.

Topics of interest include, but are not restricted to:

· Next generation sequencing bioalgorithms

· Multi-omics data analysis

· High dimensional statistical analysis of omics data

· Algorithms for alternative splicing analysis

· Algorithms for molecular evolution and phylogenetic analysis

· Methods for the visualization of high dimensional complex omic data

· Software tools for bioinformatics

· Methods for comparative genomics

· Methods for functional classification of genes

· Methods for unsupervised analysis, validation and visualization of structures discovered in bio-molecular data

· Health-Informatics and Medical Informatics

· Methods for the integration of clinical and genetic data

· Heterogeneous data integration and data fusion for diagnostics

· Algorithms for pharmacogenomics

· Biomedical text mining and imaging

· Methods for diagnosis and prognosis within personalized medicine

· Statistical methods for the analysis of clinical data

· Prediction of secondary and tertiary protein structures

· Mass spectrometry data analysis in proteomics

· Algorithms for molecular evolution and phylogenetic analysis

· Bio-molecular databases and data mining

· Mathematical modeling and automated reasoning on biological and synthetic systems

· Computational simulation of biological systems

· Methods and advances in systems biology

· Spatio-temporal analysis of synthetic and biological systems

· Network systems biology

· Models for cell populations and tissues

· Methods for the engineering of synthetic components

· Modelling and engineering of interacting synthetic and biological systems

· Software tools for bioinformatics, biostatistics, systems and synthetic biology

TUTORIALS AND SPECIAL SESSIONS

CIBB 2018 will run a number of Tutorials and Special Sessions. Any topic of interest for the conference is eligible for a tutorial. Tutorials typically last from one to three hours. Special sessions focus on a specific, possibly cutting-edge, topic of interest for CIBB 2018. Special session organisers will be responsible for call dissemination, the reviewing process and organizing oral presentations. Typically, a special session will have at least 4 accepted papers and may have an invited speaker (to be negotiated).

Tutorial proposals

⁃ including title, a one page long abstract, and short CV of presenters

⁃ due by 25th March 2018

⁃ send proposals to ⁃ cibb2018@campus.fct.unl.pt


Special Session proposals

⁃ including the session's title and scope, short CV of sessions chairs, preliminary list of at least 4, possibly more, potential authors

⁃ due by 25th March 2018

⁃ a special session is expected to have at least 4 accepted papers

⁃ send proposals to ⁃ cibb2018@campus.fct.unl.pt

PUBLICATION

Pdf versions of accepted papers will be distributed at the conference. At least one author of an accepted paper is required to register and present their paper at the conference. Authors of accepted papers will be invited to submit an extended version of their work to a post-conference monograph.

We plan to invite all papers for a volume in the Springer series of Lecture Notes in Bioinformatics (LNBI). Continuing the tradition of CIBB, we are also planning to invite the best papers, as an alternative to the publication on LNBI, to a special issue of an international scientific journal (such as BMC Bioinformatics, as in the latest editions).

Antonino Staiano, University of Naples Parthenope
antonino.staiano@uniparthenope.it
***********************************************************
URL: http://eventos.fct.unl.pt/cibb2018/

Contact Person: Antonino Staiano (antonino.staiano@uniparthenope.it)

Saturday, February 3, 2018

Second CfP Special Issue on Statistical and Machine Learning Modeling in Computational Epigenetics

Statistical and Machine Learning Modeling
in Computational Epigenetics@BioMed Research International

Epigenetics has recently emerged as one of the hottest fields in life
sciences for studying heritable change in phenotype, gene function, or gene
expression that are not directly encoded in the DNA itself. Up-to-date
studies have shown that epigenetic modulations are fundamental in many
developmental processes, from tissue and organ formation to allele-specific
gene expression. When these normal epigenetic patterns modify, pattern of
gene expression can be deregulated, and it has been proven that such
mechanisms are central in several disorders and diseases, among which are
psychiatric disorders, obesity, and etiology of a number of diseases such
as cancer, schizophrenia, and Alzheimer, just to name a few. Today, thanks
also to several large human epigenome projects, scientists have a better
understanding of the basic principles of epigenetic mechanisms as well as
their relevance to health disorders and disease. At the heart of this
fascinating research field are computational tools that, by analyzing
complex genomic information, play an essential role in discovering
evidences to define new assessable hypotheses. In particular, the
literature at a glance shows the effectiveness of a combination of
statistical and machine learning techniques in several epigenetic analyses.
This special issue aims to host original papers and reviews on recent
research advances and the state-of-the-art methods in the fields of
statistical and machine learning methodologies and algorithm design for the
study of epigenetic mechanisms. Especially welcome are also software
systems with a special emphasis on tools developed with the help of big
data distributed processing framework like Hadoop and Spark to properly
manage the huge amount of data coming from epigenome-scale experiments.

Potential topics include but are not limited to the following:Machine
learning
Statistical learning theory
Fuzzy logic and systems
Neuro-fuzzy systems
Granular computing
Data mining
Probabilistic and statistical modelling
Algorithms designed for epigenomic big data
High-throughput data in the broad context of epigenomics
Analysis, modeling, and prediction of DNA methylation patterns
Analysis, modeling, and prediction of histone modifications in DNA sequences
Identification of abnormal DNA methylation within CpG islands in different
diseases
Analysis of epigenetic marks in stem cells
Analysis of miRNA changes in cancer and other diseases
Simultaneous analysis of methylome and transcriptome
Analysis of reciprocal regulation of noncoding RNA and methylation
Study of the epigenetic role in metabolomics
Analysis of microbiome role in epigenetic regulation of gene expression

Authors can submit their manuscripts through the Manuscript Tracking System
at https://mts.hindawi.com/submit/journals/bmri/computational.biology/acim/

Submission deadline:
Friday, 2 March 2018

Publication date:
July 2018

URL: http://www.hindawi.com/journals/BMRI/si/873738/cfp/

Contact Person: Antonino Staiano (antonino.staiano@uniparthenope.it)

Monday, January 8, 2018

Save the Date: Chicago Genomics and Data Science Hackathon

From 11-13 July 2018, the NCBI will help out with a Data Science hackathon on the Northwestern School of Medicine Campus in Downtown Chicago! The hackathon will focus on genomics as well as general Data Science analyses including text, image and sequence processing. This event is for researchers, including students and postdocs, who have already engaged in the use of large datasets or in the development of pipelines for analyses from high-throughput experiments. Some projects are available to other non-scientific developers, mathematicians, or librarians.
The event is open to anyone selected for the hackathon and willing to travel to Chicago. Please note that this follows directly on the heels of the ISMB 2018 meeting.
Working groups of five to six individuals will be formed into five to eight teams. These teams will build pipelines and tools to analyze large datasets within a cloud infrastructure. Example subjects for such a hackathon include:
A machine learning tool for observing structural changes in time course light microscopy.
Novel virus discovery
Automated systematic review methodology.
Splitting BLAST databases on the cloud
Data mapping tool that assists users with mapping their data to CDEs
Disease clustering from literature based on limited training data (phenotypic information)
Variants from RNAseq (including single cell)
Graphical User Interface for Gene Expression calculated on the fly from raw data
Please go to http://ncbi-hackathons.github.io to propose projects, and to access the sign-up form when available (likely in mid-March)
URL: https://ncbi-hackathons.github.io

Contact Person: Ben Busby (ben.busby@nih.gov)