This article collection showcases recent advances in computational biology and bioinformatics, highlighting innovative methods for tackling challenges in drug discovery, disease diagnosis, and biological data interpretation. The collection spans a broad range of topics, including the development of novel machine learning models such as quadratic graph-theoretic descriptors for compound inference and hybrid deep learning frameworks for DNA-binding protein prediction; the creation of precision tools for genome size estimation; and automated imaging biomarkers to characterize tissue regeneration in wound healing. Additionally, the abstracts feature the integration of omics and high-dimensional data through approaches like joint non-negative matrix factorization to identify prognostic biomarkers, illustrated by the discovery of COPS5 for diffuse large B-cell lymphoma. Population-specific analyses, such as those unraveling genetic and immune-related mechanisms in esophageal squamous cell carcinoma among Kazakhstani patients, demonstrate the promise of transcriptome sequencing for disease understanding and early diagnosis. The collection also underscores the use of in silico pipelines for antigen selection in vaccine development against neglected diseases like fasciolopsiasis. Collectively, these studies underscore the power of advanced computational and deep learning methods to accelerate biomedical discoveries, improve predictive accuracy, and
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contribute to precision medicine by interpreting complex biological data and identifying clinically relevant targets.With the completion of the human genome project, bioinformatics has been extensively applied to various aspects of health and life sciences. With the advancement in various OMICS strategies followed by their integration, we have entered into the era where we are aiming to bridge the gap between biological data and clinical informatics, ultimately leading to improvements in human health. To achieve such an aim practically, translational bioinformatics requires revamping and sophistication of methods for storage, analysis and interpretation of the increasingly big biological data. The InCoB 2023 edition is therefore committed to provide an opportunity to the scientific community to showcase their research and deliberate on this important theme through keynote talks, presentations, plenary sessions, poster sessions, workshops, software demos, and panel discussions, among others.
This Frontiers Research Topic is focused on the theme of the 22nd International Conference on Bioinformatics (InCoB2023; https://incob.apbionet.org/incob23/), the flagship, annual conference of the Asia & Pacific Bioinformatics Network (APBioNET; https://www.apbionet.org), which is returning back to Australia after nine years, this time hosted by the Queensland University of Technology and the Translational Research Institute (TRI), Brisbane, Australia. InCoB 2023 is scheduled to be held from November 12-15, 2023 at the Translational Research Institute (TRI).
The theme of the conference is “Translational Bioinformatics, Transforming Life.” We are pleased to call upon for submissions related to the theme in all areas of bioinformatics and computational biology, which are in scope for either Frontiers in Genetics or Frontiers in Bioinformatics.
Areas which are in scope for Frontiers in Genetics:
Big data in biology: analytics, machine learning methods and datasets
Database management
Drug design and discovery
Genetics of cell differentiation and reprogramming
Genome and proteome manipulation
Genomics
Metagenomics
Microarray analysis
Molecular evolution and phylogeny
Next generation sequencing
Population genetics
Systems Biology
Areas which are in scope for Frontiers in Bioinformatics:
Structural bioinformatics
Scalable data storage
Proteomics
Synthetic Biology
Translational Bioinformatics
Workflow and knowledge management
Immunoinformatics
Medical and health informatics
High throughput omics and imaging platforms
Metabolomics
Protein interactions and diseases
Protein folding and conformational diseases
Bioimaging
Bioinformatics applications
Bioinformatics models, methods and algorithms
Biological sequence analysis
Bio-ontology and semantics
Clinical bioinformatics
Data mining and biomedical knowledge discovery
This article collection showcases recent advances in computational biology and bioinformatics, highlighting innovative methods for tackling challenges in drug discovery, disease diagnosis, and biological data interpretation. The collection spans a broad range of topics, including the development of novel machine learning models such as quadratic graph-theoretic descriptors for compound inference and hybrid deep learning frameworks for DNA-binding protein prediction; the creation of precision tools for genome size estimation; and automated imaging biomarkers to characterize tissue regeneration in wound healing. Additionally, the abstracts feature the integration of omics and high-dimensional data through approaches like joint non-negative matrix factorization to identify prognostic biomarkers, illustrated by the discovery of COPS5 for diffuse large B-cell lymphoma. Population-specific analyses, such as those unraveling genetic and immune-related mechanisms in esophageal squamous cell carcinoma among Kazakhstani patients, demonstrate the promise of transcriptome sequencing for disease understanding and early diagnosis. The collection also underscores the use of in silico pipelines for antigen selection in vaccine development against neglected diseases like fasciolopsiasis. Collectively, these studies underscore the power of advanced computational and deep learning methods to accelerate biomedical discoveries, improve predictive accuracy, and
--------
contribute to precision medicine by interpreting complex biological data and identifying clinically relevant targets.With the completion of the human genome project, bioinformatics has been extensively applied to various aspects of health and life sciences. With the advancement in various OMICS strategies followed by their integration, we have entered into the era where we are aiming to bridge the gap between biological data and clinical informatics, ultimately leading to improvements in human health. To achieve such an aim practically, translational bioinformatics requires revamping and sophistication of methods for storage, analysis and interpretation of the increasingly big biological data. The InCoB 2023 edition is therefore committed to provide an opportunity to the scientific community to showcase their research and deliberate on this important theme through keynote talks, presentations, plenary sessions, poster sessions, workshops, software demos, and panel discussions, among others.
This Frontiers Research Topic is focused on the theme of the 22nd International Conference on Bioinformatics (InCoB2023; https://incob.apbionet.org/incob23/), the flagship, annual conference of the Asia & Pacific Bioinformatics Network (APBioNET; https://www.apbionet.org), which is returning back to Australia after nine years, this time hosted by the Queensland University of Technology and the Translational Research Institute (TRI), Brisbane, Australia. InCoB 2023 is scheduled to be held from November 12-15, 2023 at the Translational Research Institute (TRI).
The theme of the conference is “Translational Bioinformatics, Transforming Life.” We are pleased to call upon for submissions related to the theme in all areas of bioinformatics and computational biology, which are in scope for either Frontiers in Genetics or Frontiers in Bioinformatics.
Areas which are in scope for Frontiers in Genetics:
Big data in biology: analytics, machine learning methods and datasets
Database management
Drug design and discovery
Genetics of cell differentiation and reprogramming
Genome and proteome manipulation
Genomics
Metagenomics
Microarray analysis
Molecular evolution and phylogeny
Next generation sequencing
Population genetics
Systems Biology
Areas which are in scope for Frontiers in Bioinformatics:
Structural bioinformatics
Scalable data storage
Proteomics
Synthetic Biology
Translational Bioinformatics
Workflow and knowledge management
Immunoinformatics
Medical and health informatics
High throughput omics and imaging platforms
Metabolomics
Protein interactions and diseases
Protein folding and conformational diseases
Bioimaging
Bioinformatics applications
Bioinformatics models, methods and algorithms
Biological sequence analysis
Bio-ontology and semantics
Clinical bioinformatics
Data mining and biomedical knowledge discovery