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This book features 21 papers spanning many different sub-fields in
bioinformatics and computational biology, presenting the latest
research on the practical applications to promote fruitful
interactions between young researchers in different areas related
to the field. Next-generation sequencing technologies, together
with other emerging and diverse experimental techniques, are
evolving rapidly, creating numerous types of omics data. These, in
turn, are creating new challenges for the expanding fields of
bioinformatics and computational biology, which seek to analyse,
process, integrate and extract meaningful knowledge from such data.
This calls for new algorithms and approaches from fields such as
databases, statistics, data mining, machine learning, optimization,
computer science, machine learning and artificial intelligence.
Clearly, biology is increasingly becoming a science of information,
requiring tools from the computational sciences. To address these
challenges, we have seen the emergence of a new generation of
interdisciplinary scientists with a strong background in the
biological and computational sciences. In this context, the
interaction of researchers from different scientific areas is, more
than ever, vital to boost the research efforts in the field and
contribute to the training of the new generation of
interdisciplinary scientists.
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Computational Mathematics Modeling in Cancer Analysis - First International Workshop, CMMCA 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings (Paperback, 1st ed. 2022)
Wenjian Qin, Nazar Zaki, Fa Zhang, Jia Wu, Fan Yang
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R1,470
Discovery Miles 14 700
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Ships in 12 - 17 working days
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This book constitutes the proceedings of the First Workshop on
Computational Mathematics Modeling in Cancer Analysis (CMMCA2022),
held in conjunction with MICCAI 2022, in Singapore in September
2022. Due to the COVID-19 pandemic restrictions, the CMMCA2022 was
held virtually. DALI 2022 accepted 15 papers from the 16
submissions that were reviewed. A major focus of CMMCA2022 is to
identify new cutting-edge techniques and their applications in
cancer data analysis in response to trends and challenges in
theoretical, computational and applied aspects of mathematics in
cancer data analysis.
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