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Advancements in Computational Biology and Bioinformatics
1. AN ANALYSIS OF RECENT ADVANCEMENTS IN
COMPUTATIONAL BIOLOGY
AND BIOINFORMATICS
AnAcademic presentation by
Dr. NancyAgnes, Head, Technical Operations,
Pubrica Group: www.pubrica.com
Email: sales@pubrica.com
3. IN-
BRIEF
A wide range of scientific topics were covered, with bioinformatics
receiving significant attention due to its rapid growth and growing
necessity in biological data processing, particularly for huge omics
datasets.
Bioinformatics refers to using information technology and
computers to huge molecular biology data sets.
Bioinformatics is expected to be a cutting-edge part of the
biotechnology sector that will aid medication development
and individualized medical treatments.
Artificial intelligence and computer science are strongly
related to microbiology and genetics in this subject.
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4. INTRODUCTI
ON
Computer biology and bioinformatics are multidisciplinary fields
that create and use computational methods to analyze massive
quantities of biological data, such as genetic sequences,cell
populations, or protein samples, to make predictions or find novel
biology.
Analytical approaches, mathematical modelling, and simulation
are the computational methods employed.
contd...
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5. In bioinformatics and computational biology, extracting intrinsic
meaningful knowledge from huge omics data remains a formidable
task. Deep learning, an emerging field of machine learning, has
demonstrated exceptional performance in various academic and
industrial applications.
We emphasize the differences and similarities in frequently used
deep learning models by addressing their basic architecture and
examining different uses and drawbacks. We anticipate that the
study will be useful infurther developingits theory, method, and
applicationin bioinformatics and computational biology.
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6. SYSTEMATIC REVIEW
WRITING
Bioinformatics fosters opportunities for discoveries and offers avenues for biological investigations
through data analysis. To provide exact results, Research writing a systematic review on this topic
relies heavily on high-quality databases. However, most biological databases contain easily
accessible errors, such as incorrectly categorized data or insufficient information.
These errors might be serious. Recent data mining methods may use the filter data. However, these
algorithms occasionally cannot cure these errors, resulting in serious analytical issues. A solution to
this challenge is manual data curation and data extraction from books.
A database of mutation effects on protein-ligand affinities, for example, was created after a thorough
review of
the literature. Nonetheless, the manual analysis may address the danger of
bias.
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contd..
.
7. Manual curation also allows for detecting errors and, where feasible, their correction.
As a result, systematic literature reviews were employed to gather data for bioinformatics analysis.
A systematic review is a strategy for discovering, estimating, and summarizing the state-of-the-art of a
certain topic in the literature. Systematic review writing helps in the constrained gathering of literature
material, allowing for a thorough methodological examination with less bias than typical reviews.
A systematic review aims to develop a comprehensive picture of a specific subject and provide
a good literature summary.
Following a pre-established and well-defined process while conducting systematic reviews is critical.
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9. COMPUTING IN
BIOINFORMATICS AND
COMPUTATIONAL BIOLOGY:
Bioinformatics and computational biology are emerging sciences
that have recently made conductinga systematic review wave in
technology sectors and the media.
They are two of the few disciplines that need a broad range of
expertise, frombiology to computing.
Wikipedia defines bioinformatics as "applying techniques from
applied mathematics, informatics, statistics, computer science,
chemistry, and biochemistry to address biological issues,
generally at the molecular
level.
"
contd..
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10. Numerous articles and essays on the subject have been produced, but locating excellent ones is like
hunting
for needles in a haystack.
This issue is addressed in Parallel Computing for Bioinformatics and Computational Biology, a
meticulous compilation of 29 articles and publications.
The articles were divided into five categories: Algorithms, Sequence Analysis, Phylogenetics, Protein
folding, and Technological platforms.
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11. STRUCTURAL BIOINFORMATICS:
MOLECULAR FOLDING, MODELLING,
AND DESIGN
Oneof themostcommonbioinformaticsapplicationsclinical trial
systematic review services is the identification of three-dimensional
structure, protein molecular modelling, and folding to forecast the
possible function of proteins or model the behaviour of molecules, and
other molecular structures, fold the molecule to its natural biologically
functional three-dimensional structure and assist in the development of
biomedical drugs for various complicated human diseases.
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12. Bioinformatics is one of several scientific disciplines where the
principles of network topology have found extensive application.
As a result, large-scale biological networks, such as the biome,
interactome, and microbiome, have been created.
BIOLOGICAL
NETWORKS AND
SYSTEM BIOLOGY
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13. SOFTWARE, ANALYSIS TOOLS,
SERVICES, AND WORKFLOW
Theprimaryforce behindthecurrentandfuture advancementof
bioinformaticstools andsoftware is theadvancementof genome
decoding technologies, which is necessary for their analyses, the
accumulation of large volumes of biological data, and the development
of computer technologies, including networking, visualization, graphics,
and molecular modelling.
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14. TEXT
MINING
The increasing volume of biomedical literature is being gathered,
constructed, and organized using computer algorithms and
bioinformatics tools.
This encourages scientists to query, mine, examine, and synthesize the
specific literature and published articles of their research interest.
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15. CONCLUSI
ON
Systematic literature reviews were done to gather information for
bioinformatics analysis. It is a method for determining, estimating, and
summarizing the current status of a certain literary topic.
In contrast to traditional reviews, systematic literature reviews allow for
the selective collection of literature material, enabling a rigorous
methodological analysis with less prejudice.
Theobjective is to understandaparticular issueandprovideafair
assessmentof theliterature.Asaresult, adheringto apre-established
and well-stated process while conducting systematic reviews is crucial.
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16. ABOUT
PUBRICA
Scientific andmedicalresearchpapersare producedbytheteamof
researchersandwriters at Pubrica,andtheymaybeinvaluable sources
for authors and practitioners.
Pubrica medical writers help you create and modify the introduction by
using the reader to alert them to the gaps in the selected study subject.
Our experts know the sequence in which the topic where the hypothesis
is given is followed by the broad subject, the issue, and the backdrop.
16
pag
e
17. REFEREN
CES
1.Fu, Yuanyuan, et al. "Current trend and development in bioinformatics
research." BMC Bioinformatics 21.9 (2020): 1-
3.
2.Zomaya,A. Y. (2005). Parallel computingfor bioinformaticsand
computational biology. Wiley.
3.Vega-
Rodríguez MA, Rubio-
Largo Á. Parallelismin computational biology:
Aview from diverse high-performance computing applications. The
International Journal of High Performance ComputingApplications.
2018;32(3):317-320. doi:10.1177/1094342016677599
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