Computational Biology for Stem Cell Research
portes grátis
Computational Biology for Stem Cell Research
Kumar, Rajesh; Sharma, Navneet; Raghav, Pawan; Lathwal, Anjali
Elsevier Science Publishing Co Inc
01/2024
566
Mole
Inglês
9780443132223
15 a 20 dias
Descrição não disponível.
Section I - In silico Tools and Approaches in Stem Cell Biology
1. Advancement of In Silico Tools in Stem Cell Research
2. Paradigm shift in stem cell research with computational tools, techniques, and databases
3. Stem Cell Informatics: Web-Resources Aiding in Stem Cell Research
4. Stem Cell-Based Informatics Development and Approaches
5. Application of Machine Learning-Based Approaches in Stem Cell Research
6. Stem Cell Therapy in the Era of Machine Learning
7. Computational and Stem Cell Biology: Challenges and Future Perspectives
Section II - Application of Genomic and Proteomic Approaches in Stem Cell Research
8. Single Cell Transcriptome Profiling in Unravelling Distinct Molecular Signatures from Cancer Stem Cells 9. The Single-Cell Big Data Analytics: A Game-Changer in Bioscience
10. Unravelling the genomics and proteomics aspects of the stemness phenotype in stem cells
11. Cutting-Edge Proteogenomics Approaches to Analyze Stem Cells at the Therapeutic Level
12. Advances in Regenerative Medicines Based on Mesenchymal Stem Cell Secretome
13. Paradigms of Omics in Bioinformatics for Accelerating Current Trends and Future Prospects of Stem Cell Research
14. Transcriptomic Profiling-Based Identification Biomarkers of Stem Cells
15. Genomic and Transcriptomic Applications in Neural Stem Cell Therapeutics
Section III - Stem Cell Network Modeling and Systems Biology
16. Integration of Multi-omic Data to Identify Transcriptional Targets During Human Hematopoietic Stem Cell Differentiation
17. Computational Approaches to Determine Stem Cell Fate
18. Stem Cell Databases and Tools: Challenges and Opportunities for Computational Biology
19. Deciphering the Complexities of Stem Cells Through Network Biology Approaches for their Application in Regenerative Medicine
20. Bioinformatics Approaches to the Understanding of Notch Signaling in the Biology of Stem Cells
21. In Silico Approaches for the Analyses of Developmental Fate of Stem Cells
22. Exploring imaging technologies and computational resources in stem cell research for regenerative medicine: A comprehensive review
23. Computational Approaches for Hematopoietic Stem Cells: Advancing Regenerative Therapeutics
24. Approaches to Construct and Analyze Stem Cells Regulatory Networks
Section IV - Computational Approaches for Stem Cell Tissue Engineering
25. Tissue Engineering in Chondral Defect
26. Recent Advances in Computational Modeling: An Appraisal of Stem Cell and Tissue Engineering Research
27. Computational Approaches for Bioengineering of Cornea
28. Cheminformatics, Metabolomics and Stem Cell Tissue Engineering: A Transformative Insight
29. Targeting Cancer Stem Cells and Harnessing of Computational Tools Offer New Strategies for Cancer Therapy
30. Introduction to Machine Learning and its Applications in Stem Cell Research
31. Multiscale Computational and Machine Learning Models for Designing Stem Cell-Based Regenerative Medicine Therapies
32. Computational Analysis of Epithelial Tissue Regeneration
1. Advancement of In Silico Tools in Stem Cell Research
2. Paradigm shift in stem cell research with computational tools, techniques, and databases
3. Stem Cell Informatics: Web-Resources Aiding in Stem Cell Research
4. Stem Cell-Based Informatics Development and Approaches
5. Application of Machine Learning-Based Approaches in Stem Cell Research
6. Stem Cell Therapy in the Era of Machine Learning
7. Computational and Stem Cell Biology: Challenges and Future Perspectives
Section II - Application of Genomic and Proteomic Approaches in Stem Cell Research
8. Single Cell Transcriptome Profiling in Unravelling Distinct Molecular Signatures from Cancer Stem Cells 9. The Single-Cell Big Data Analytics: A Game-Changer in Bioscience
10. Unravelling the genomics and proteomics aspects of the stemness phenotype in stem cells
11. Cutting-Edge Proteogenomics Approaches to Analyze Stem Cells at the Therapeutic Level
12. Advances in Regenerative Medicines Based on Mesenchymal Stem Cell Secretome
13. Paradigms of Omics in Bioinformatics for Accelerating Current Trends and Future Prospects of Stem Cell Research
14. Transcriptomic Profiling-Based Identification Biomarkers of Stem Cells
15. Genomic and Transcriptomic Applications in Neural Stem Cell Therapeutics
Section III - Stem Cell Network Modeling and Systems Biology
16. Integration of Multi-omic Data to Identify Transcriptional Targets During Human Hematopoietic Stem Cell Differentiation
17. Computational Approaches to Determine Stem Cell Fate
18. Stem Cell Databases and Tools: Challenges and Opportunities for Computational Biology
19. Deciphering the Complexities of Stem Cells Through Network Biology Approaches for their Application in Regenerative Medicine
20. Bioinformatics Approaches to the Understanding of Notch Signaling in the Biology of Stem Cells
21. In Silico Approaches for the Analyses of Developmental Fate of Stem Cells
22. Exploring imaging technologies and computational resources in stem cell research for regenerative medicine: A comprehensive review
23. Computational Approaches for Hematopoietic Stem Cells: Advancing Regenerative Therapeutics
24. Approaches to Construct and Analyze Stem Cells Regulatory Networks
Section IV - Computational Approaches for Stem Cell Tissue Engineering
25. Tissue Engineering in Chondral Defect
26. Recent Advances in Computational Modeling: An Appraisal of Stem Cell and Tissue Engineering Research
27. Computational Approaches for Bioengineering of Cornea
28. Cheminformatics, Metabolomics and Stem Cell Tissue Engineering: A Transformative Insight
29. Targeting Cancer Stem Cells and Harnessing of Computational Tools Offer New Strategies for Cancer Therapy
30. Introduction to Machine Learning and its Applications in Stem Cell Research
31. Multiscale Computational and Machine Learning Models for Designing Stem Cell-Based Regenerative Medicine Therapies
32. Computational Analysis of Epithelial Tissue Regeneration
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Stem Cells; Mesenchymal Stem Cells; Hematopoietic Stem Cells; Cancer Stem Cells; Computational Biology; Tissue Engineering; Bioinformatics; Nanoinformatics; Microinformatics; Transplantation; In silico; Systems Biology; Machine Learning
Section I - In silico Tools and Approaches in Stem Cell Biology
1. Advancement of In Silico Tools in Stem Cell Research
2. Paradigm shift in stem cell research with computational tools, techniques, and databases
3. Stem Cell Informatics: Web-Resources Aiding in Stem Cell Research
4. Stem Cell-Based Informatics Development and Approaches
5. Application of Machine Learning-Based Approaches in Stem Cell Research
6. Stem Cell Therapy in the Era of Machine Learning
7. Computational and Stem Cell Biology: Challenges and Future Perspectives
Section II - Application of Genomic and Proteomic Approaches in Stem Cell Research
8. Single Cell Transcriptome Profiling in Unravelling Distinct Molecular Signatures from Cancer Stem Cells 9. The Single-Cell Big Data Analytics: A Game-Changer in Bioscience
10. Unravelling the genomics and proteomics aspects of the stemness phenotype in stem cells
11. Cutting-Edge Proteogenomics Approaches to Analyze Stem Cells at the Therapeutic Level
12. Advances in Regenerative Medicines Based on Mesenchymal Stem Cell Secretome
13. Paradigms of Omics in Bioinformatics for Accelerating Current Trends and Future Prospects of Stem Cell Research
14. Transcriptomic Profiling-Based Identification Biomarkers of Stem Cells
15. Genomic and Transcriptomic Applications in Neural Stem Cell Therapeutics
Section III - Stem Cell Network Modeling and Systems Biology
16. Integration of Multi-omic Data to Identify Transcriptional Targets During Human Hematopoietic Stem Cell Differentiation
17. Computational Approaches to Determine Stem Cell Fate
18. Stem Cell Databases and Tools: Challenges and Opportunities for Computational Biology
19. Deciphering the Complexities of Stem Cells Through Network Biology Approaches for their Application in Regenerative Medicine
20. Bioinformatics Approaches to the Understanding of Notch Signaling in the Biology of Stem Cells
21. In Silico Approaches for the Analyses of Developmental Fate of Stem Cells
22. Exploring imaging technologies and computational resources in stem cell research for regenerative medicine: A comprehensive review
23. Computational Approaches for Hematopoietic Stem Cells: Advancing Regenerative Therapeutics
24. Approaches to Construct and Analyze Stem Cells Regulatory Networks
Section IV - Computational Approaches for Stem Cell Tissue Engineering
25. Tissue Engineering in Chondral Defect
26. Recent Advances in Computational Modeling: An Appraisal of Stem Cell and Tissue Engineering Research
27. Computational Approaches for Bioengineering of Cornea
28. Cheminformatics, Metabolomics and Stem Cell Tissue Engineering: A Transformative Insight
29. Targeting Cancer Stem Cells and Harnessing of Computational Tools Offer New Strategies for Cancer Therapy
30. Introduction to Machine Learning and its Applications in Stem Cell Research
31. Multiscale Computational and Machine Learning Models for Designing Stem Cell-Based Regenerative Medicine Therapies
32. Computational Analysis of Epithelial Tissue Regeneration
1. Advancement of In Silico Tools in Stem Cell Research
2. Paradigm shift in stem cell research with computational tools, techniques, and databases
3. Stem Cell Informatics: Web-Resources Aiding in Stem Cell Research
4. Stem Cell-Based Informatics Development and Approaches
5. Application of Machine Learning-Based Approaches in Stem Cell Research
6. Stem Cell Therapy in the Era of Machine Learning
7. Computational and Stem Cell Biology: Challenges and Future Perspectives
Section II - Application of Genomic and Proteomic Approaches in Stem Cell Research
8. Single Cell Transcriptome Profiling in Unravelling Distinct Molecular Signatures from Cancer Stem Cells 9. The Single-Cell Big Data Analytics: A Game-Changer in Bioscience
10. Unravelling the genomics and proteomics aspects of the stemness phenotype in stem cells
11. Cutting-Edge Proteogenomics Approaches to Analyze Stem Cells at the Therapeutic Level
12. Advances in Regenerative Medicines Based on Mesenchymal Stem Cell Secretome
13. Paradigms of Omics in Bioinformatics for Accelerating Current Trends and Future Prospects of Stem Cell Research
14. Transcriptomic Profiling-Based Identification Biomarkers of Stem Cells
15. Genomic and Transcriptomic Applications in Neural Stem Cell Therapeutics
Section III - Stem Cell Network Modeling and Systems Biology
16. Integration of Multi-omic Data to Identify Transcriptional Targets During Human Hematopoietic Stem Cell Differentiation
17. Computational Approaches to Determine Stem Cell Fate
18. Stem Cell Databases and Tools: Challenges and Opportunities for Computational Biology
19. Deciphering the Complexities of Stem Cells Through Network Biology Approaches for their Application in Regenerative Medicine
20. Bioinformatics Approaches to the Understanding of Notch Signaling in the Biology of Stem Cells
21. In Silico Approaches for the Analyses of Developmental Fate of Stem Cells
22. Exploring imaging technologies and computational resources in stem cell research for regenerative medicine: A comprehensive review
23. Computational Approaches for Hematopoietic Stem Cells: Advancing Regenerative Therapeutics
24. Approaches to Construct and Analyze Stem Cells Regulatory Networks
Section IV - Computational Approaches for Stem Cell Tissue Engineering
25. Tissue Engineering in Chondral Defect
26. Recent Advances in Computational Modeling: An Appraisal of Stem Cell and Tissue Engineering Research
27. Computational Approaches for Bioengineering of Cornea
28. Cheminformatics, Metabolomics and Stem Cell Tissue Engineering: A Transformative Insight
29. Targeting Cancer Stem Cells and Harnessing of Computational Tools Offer New Strategies for Cancer Therapy
30. Introduction to Machine Learning and its Applications in Stem Cell Research
31. Multiscale Computational and Machine Learning Models for Designing Stem Cell-Based Regenerative Medicine Therapies
32. Computational Analysis of Epithelial Tissue Regeneration
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
