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Science

Computational Biology at IgMin Research | Science Group

Our mission is to foster interdisciplinary dialogue and accelerate the advancement of knowledge across a wide spectrum of scientific domains.

About

Computational Biology is a dynamic and interdisciplinary field that merges biology, mathematics, computer science, and statistics to tackle complex biological questions. This discipline harnesses the power of computational methods and algorithms to analyze biological data, model biological processes, and make predictions about living systems.

Computational biologists develop innovative tools for tasks such as sequence analysis, structure prediction, pathway modeling, and systems biology. By integrating data from genomics, proteomics, and other 'omics' fields, computational biology sheds light on the intricacies of biological networks and offers insights into disease mechanisms, drug discovery, and evolution. This field is at the forefront of modern biological research, transforming data into knowledge and accelerating scientific discovery.

  • Sequence analysis
  • Structural bioinformatics
  • Protein folding simulations
  • Genomic data analysis
  • Phylogenetics
  • Evolutionary genomics
  • Systems biology modeling
  • Biological network analysis
  • Molecular dynamics simulations
  • Metagenomics
  • Computational drug discovery
  • Structural genomics
  • Comparative genomics
  • Pathway analysis
  • Functional genomics
  • Bioinformatics databases
  • Epigenomics
  • Machine learning in biology
  • Synthetic biology modeling
  • Computational immunology
  • Computational cancer biology
  • Computational neuroscience
  • Computational biology education and outreach
  • Advancements in computational biology
  • Computational biology and precision medicine

Science Group (2)

Mini Review Article ID: igmin174
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Open Access Policy refers to a set of principles and guidelines aimed at providing unrestricted access to scholarly research and literature. It promotes the free availability and unrestricted use of research outputs, enabling researchers, students, and the general public to access, read, download, and distribute scholarly articles without financial or legal barriers. In this response, I will provide you with an overview of the history and latest resolutions related to Open Access Policy.

The use of FIKR (Facet, Insight, Knowledge, and Resilience) Personality as an Effective Assessment Tool to Select the Best Leadership in an Organization
by Chee Kong Yap, Chee Seng Leow and Wing Sum Vincent Leong

This study presents a new assessment tool, FIKR (Facet, Insight, Knowledge, and Resilience) Personality Traits (PTs) for organisational talent development and leadership. The FIKR assessment tool offers a thorough framework for developing talent and leadership, covering facets, insights, knowledge, and resilience. By using these elements, individuals can enhance their ability to successfully and strategically guide and influence others. Gaining self-awareness of one’s strengths and shortcomings, harmonising personal values with objectives... for developing talents, obtaining the requisite information and abilities, and cultivating resilience not only promotes personal progress but also cultivates the potential of people within the organisation. By embracing the interaction of these FIKR characteristics, one may adopt a comprehensive and influential approach to talent development and leadership.

Sustainable Chemistry Computational Biology
Research Article Article ID: igmin133
Cite

Open Access Policy refers to a set of principles and guidelines aimed at providing unrestricted access to scholarly research and literature. It promotes the free availability and unrestricted use of research outputs, enabling researchers, students, and the general public to access, read, download, and distribute scholarly articles without financial or legal barriers. In this response, I will provide you with an overview of the history and latest resolutions related to Open Access Policy.

Analytical Expressions of the Markov Chain of K-Ras4B Protein within the Catalytic Environment and a New Markov-State Model
by Orchidea Maria Lecian

The finite Markov chain to which there correspond the qualities of the conformational dynamics of the K-Ras4B proteins in the catalytic reaction is written. The corresponding Markov-Sates models are studied. The properties of the K-Ras4B processes Markov chain allow one to define a new two-state MSM for the analytical description of the final-state transition. The time evolution of the eigenvalue corresponding to the final-state transition in the Galerkin description is written. The tools for the analytical calculations of the relative error ...are therefore prepared. New analytical formulations of the time evolution of the eigenvalue corresponding to the final-state transition are newly written from the experimental data and form the properties of the lag time in shaping the discretization error. The features of the discretization error are newly studied. A comparison with the experimental data is proposed.

Computational Biology Molecular BiologyBiophysics