
Proteomics, Multi-Omics and Systems Biology in Optic Nerve Regeneration
- 1st Edition - January 15, 2025
- Imprint: Academic Press
- Editor: Sanjoy K. Bhattacharya
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 1 5 5 8 0 - 2
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 1 5 5 8 1 - 9
Proteomics, Multi-Omics and Systems Biology in Optic Nerve Regeneration is a comprehensive reference that covers all vistas of standardization of axon regeneration, as well as a… Read more

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Request a sales quoteProteomics, Multi-Omics and Systems Biology in Optic Nerve Regeneration is a comprehensive reference that covers all vistas of standardization of axon regeneration, as well as all multi-omics and system level data and integration tools. By adopting a translational approach, the book bridges current research in the field to clinical applications, and readers can expect to learn standardization approaches for axon regeneration, multi-omics datasets, different databases, search engines, multiple dataset integrative tools, pathway convergence approaches and tools, outcome and outcome measures that unify bench research with clinical outcome.
The axon regeneration from existing neurons in central nervous system (CNS) have become a potential possibility in the last decade. The potential possibility of long-distance axon growth has opened the possibility of re-connectivity of axons of retinal ganglion cell neurons within the lateral geniculate nucleus in the brain. The long-distance axon regeneration and re-connectivity is a promise to restore lost vision in the optic nerve. Further, long-distance regeneration and re-innervation is equally helpful for other fields such as spinal cord injuries.
- Includes updates on the use of multi-omics datasets for selecting molecules for axon regeneration
- Bridges the preclinical and clinical world, from selection of the molecules to outcome leading to IND filing and their use
- Includes system level knowledge needed for central nervous system axon and dendrite regeneration, and standardizes the system level biology for axon regeneration
- Explores the current state of multi-omics in axon and dendrite regeneration in the optic nerve and its comparison to other CNS regeneration
Researchers engaged in neuro-regeneration including graduate students and ophthalmologists who are actively working in neuro-regeneration, glaucoma, traumatic optic neuropathies, bioinformaticians, systems biologists, proteomics, Basic scientists working on axon/dendrite regeneration, Clinicians, Ophthalmologists, Researchers in other neuro-degeneration fields (Alzeheimer’s diabetic peripheral neuropathy), Neuroscientists, Medical doctors who are working in the fields of Neuroscience, Scientists who are working in neuro-regeneration, researchers
- Title of Book
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- Contributors
- About the editor
- Preface
- Acknowledgments
- Section I. Historic accounts of neuron regeneration
- Chapter 1. Historic accounts of neuron regeneration
- 1 Developmental discoveries in neurobiology
- 1.1 Functional recovery in the age of enlightenment
- 2 The advent of microscopy
- 2.1 Invention of the ophthalmoscope
- 2.2 Impact of microscopy and Ranvier's legacy
- 2.3 Camilo Golgi's black reaction
- 2.4 Wallerian Degeneration
- 2.5 Nerve discoveries after median and ulnar nerve injury
- 2.6 The optic nerve as a central nervous system entity
- 3 Twentieth-century revelations
- 3.1 The impact of injuries on turn of century research
- 3.2 Monogenist versus polygenist schools of thought
- 3.3 Nerve grafts within the CNS
- 4 The possibility of CNS regeneration?
- 5 The golden age and onward
- Section II. Reagents for neuron regeneration structural studies
- Chapter 2. Imaging methods for monitoring optic nerve regeneration
- 1 Introduction
- 2 Current ex vivo labeling techniques
- 2.1 Carbocyanines for neuronal labeling
- 2.2 Cholera toxin subunit B for anterograde and retrograde axonal tracing
- 2.3 Bromodeoxyuridine for identifying neuronal regeneration
- 2.4 Viral vectors as an alternative to traditional approaches
- 3 In vivo MRI tracers
- 3.1 Manganese-enhanced magnetic resonance imaging of optic nerve regeneration
- 3.2 Iron oxide nanoparticles for tracking stem cells for optic nerve regeneration
- 3.3 Gadolinium-enhanced MRI as a zinc sensor in optic nerve regeneration
- 4 Noninvasive MRI monitoring
- 4.1 Structural monitoring
- 4.2 Functional monitoring
- 5 Limitations and future directions
- Chapter 3. Multimodal translational imaging of central nervous system structure and function and its integrative value in neuroregeneration strategies
- 1 Introduction
- 2 Classification of MRI approaches
- 2.1 Conventional MRI
- 2.2 Diffusion tensor imaging
- 2.3 Functional magnetic resonance imaging
- 2.4 Molecular imaging
- 2.4.1 MRI with super paramagnetic nanoparticles
- 2.4.2 Magnetic resonance spectroscopy
- 3 Radiomics and artificial intelligence
- 4 Integration of translational imaging with genomics, proteomics, and metabolomics
- 5 Conclusion
- Chapter 4. Staining reagents for neuronal degeneration and axon regeneration studies
- 1 Introduction
- 2 Labeling regeneration
- 2.1 Cholera toxin subunit B
- 2.2 Retrograde labeling with fluorogold
- 2.3 GAP43
- 3 Immunohistochemistry
- 3.1 Detection and visualization
- 3.2 Immunohistochemistry in nerve regeneration
- 3.3 Fluorescence in situ hybridization
- 4 Conclusion
- Chapter 5. Single cell resolution imaging techniques in optic nerve models in vivo and in vitro
- 1 Introduction
- 2 Recent developments to study optic nerve degeneration (in vivo, ex vivo, and in vitro models)
- 2.1 Imaging of ex vivo models
- 2.1.1 RGC culture model
- 2.1.2 Optic nerve explant culture
- 2.1.3 Organotypic retinal explant culture
- 2.1.4 Microfluidic chip-based models
- 2.2 Imaging of in vivo models
- 2.3 Imaging of in vitro model
- 2.3.1 Elevated hydrostatic pressure (EHP) based model
- 2.3.2 Hypoxia and oxidative stress-based models
- 2.3.3 Genetically modified hPSC cell model
- 2.3.4 Microfluidic chip model
- 3 Conclusion and perspective
- Section III. Assessments for functional regeneration
- Chapter 6. In vitro methods for assessment of retinal ganglion cell (RGC) axon growth: primary RGC isolation, culture, and high-content screening
- 1 Introduction
- 2 The two-step immunopanning protocol and its modifications
- 2.1 RGC immunopanning skeleton procedure and its modifications
- 2.2 Antibodies for the immunopanning
- 2.3 Enzymatic treatment of retinas
- 2.4 Immunopanning procedure and release adherent cells from the petri dish
- 3 How to culture RGCs
- 4 Primary RGC culture purity and how to assess it
- 5 RGC neurite outgrowth
- 6 Primary RGC cultures and high-content screening
- Chapter 7. Double-edge sword: Positive and negative effects of inflammation on axonal regeneration
- 1 Introduction
- 2 Key inflammatory cell types
- 2.1 Microglia
- 2.2 Macrophages
- 2.3 Muller glia
- 2.4 Astrocytes
- 2.5 Neutrophils
- 3 Key inflammatory proteins and signaling pathways that regulate axonal regeneration
- 3.1 NLRP3 inflammasome
- 3.2 STAT3/CNTF
- 3.3 Oncomodulin/SDF-1
- 3.4 Toll-like receptors
- 3.5 Wnt signaling
- 4 Conclusion
- Abbreviations
- Section IV. In vivo models and pharmacological reagents
- Chapter 8. Invertebrate models of nervous system regeneration
- 1 Introduction
- 2 Regeneration of many cells/general brain regions
- 2.1 Planaria
- 2.2 Echinoderms
- 2.3 Mollusks
- 2.4 Drosophila melanogaster
- 3 Targeted axon injury models
- 3.1 Mollusk
- 3.2 Drosophila melanogaster
- 3.3 Caenorhabditis elegans
- 4 Dendrite injury models
- 4.1 Drosophila melanogaster
- 4.2 Caenorhabditis elegans
- 5 Conclusion
- Author contributions
- Chapter 9. Optic nerve regeneration in regeneration-capable vertebrates: Lessons from high-throughput genomic studies
- 1 Introduction
- 2 Animal models of optic nerve regeneration
- 3 Approaches and challenges to describing changes in gene expression during regeneration
- 4 Key findings from gene expression profiling
- 4.1 The early steps of immunological responses
- 4.2 Axon regrowth, subcellular localization, and trafficking
- 4.3 Novel noncoding RNAs
- 5 Epigenomics
- 5.1 Regulation of RAGs is not only a recapitulation of development
- 5.2 Transcription factors and chromatin regulators binding to distal enhancers mediate changes in cellular state
- 5.3 Genomics methods for identifying gene enhancers
- 5.4 Hierarchical gene regulatory modules govern temporal patterning of RAGs in zebrafish
- 5.5 Epigenetic mechanisms control chromatin accessibility and transcription in neurons
- 5.6 Using CRISPR/cas9 to manipulate chromatin and epigenetics
- 5.7 Topologically associating domains govern the gene regulatory reach of enhancers and target genes
- 6 Other high-throughput approaches
- 7 Conclusion
- Chapter 10. Electrostimulation-based strategies for axon regeneration in the central nervous system
- 1 Introduction
- 2 The visual system
- 3 Barriers to CNS regeneration
- 3.1 Cell-intrinsic barriers
- 3.2 Cell-extrinsic barriers
- 4 Limitations to current regenerative programs
- 5 Electric fields and the nervous system
- 5.1 Endogenous EFs
- 5.2 Exogenous EFs
- 5.3 Role of EFs in CNS regeneration
- 6 Electric field stimulation in vision
- 6.1 EFs promote RGC survival
- 6.2 EFs drive RGC axon regeneration and provide directional cues
- 6.3 EFs promote synaptogenesis and plasticity
- 7 Proposed mechanism of electric field stimulation effects
- 7.1 Neuroprotection
- 7.2 Axon regeneration and guidance
- 7.3 Synaptogenesis and plasticity
- 8 Electric field stimulation parameters
- 9 Conclusion
- Chapter 11. Electroceuticals and optogenetics for neuroprotection, vision preservation and restoration
- 1 Introduction to glaucoma
- 2 Neuroprotection for GON treatment: Concepts and progress
- 2.1 OHT and GON treatment using gene therapeutics
- 2.2 IOP reduction, neuroprotection, and regeneration via electrical stimulation/wave therapeutics
- 2.3 Conclusions for electroceuticals for glaucoma and OHT treatment
- 3 Introduction to optogenetics technology
- 3.1 Retinal neuroprotection and regeneration of optic nerve via optogenetic stimulation
- 3.2 Optogenetic stimulation for controlling IOP
- 3.3 Delivery of optogenes
- 3.4 Optogenetic therapy in clinic
- 3.5 Different aspects of vision restored via optogenetics
- 4 Conclusion for optogenetic vision restoration in retinal degenerative diseases and glaucoma
- Section V. Systems biology approaches
- Chapter 12. Proteome of axon transport
- 1 Introduction
- 2 Introduction to axon transport research
- 3 Proteomics toolbox and advancements
- 3.1 Axoplasmic sample preparation
- 3.2 Comparative quantitative proteomics
- 4 Axonal transportomics
- 4.1 Characterizing cargo of motor transport
- 4.1.1 Protein cargo
- 4.1.2 Organelle cargo
- 4.1.3 mRNA cargo
- 4.2 How does neurodegeneration alter the transportome?
- 4.3 How does the transportome change after injury?
- 4.4 What can the transportome uncover about survival?
- 4.5 What can the transportome uncover about regeneration?
- 5 Conclusion and future questions
- Chapter 13. Transcriptomics of optic nerve regeneration
- 1 Introduction
- 2 Microarrays
- 3 Bulk RNA sequencing
- 4 Single-cell RNA sequencing
- 5 From transcriptomics to multiomics
- Chapter 14. Single-cell transcriptomics-enabled advances in experimental optic nerve axon regeneration research
- 1 Introduction
- 2 Classification of RGCs into subtypes
- 3 Insights from scRNA-seq into novel axon regeneration-regulating genes
- 4 Why Pten inhibition stimulates only a small subset of RGCs to regenerate long-distance axons
- 5 Features of ipRGC subtypes that respond to Pten inhibition by regenerating long-distance axons
- 6 Dynlt1a and Lars2 are upregulated by Pten inhibition in ipRGCs and promote axon regeneration
- 7 Non-ipRGC subtypes and other neuronal types that could regenerate axons
- 8 Insights from scRNA-seq studies into the effect of axonal injury on neuronal subtypes and markers
- 9 scRNA-seq studies elucidate the roles of non-neuronal cells in regulating axon regeneration
- 10 Conclusion
- Chapter 15. Lessons from proteomics and phosphoproteomics on axon growth and regeneration
- 1 Introduction
- 2 How are important findings acquired using proteomics and phosphoproteomics?
- 2.1 Costs of axon regeneration from the point of view of metabolism
- 2.1.1 De novo synthesis of proteins and lipids
- 2.1.2 Axonal transport
- 2.1.3 Protein phosphorylation
- 2.1.4 Other ATP-dependent processes
- 2.2 Phosphoproteins and intrinsically disordered proteins/regions (IDP/IDR)
- 2.2.1 Molecules containing large IDRs
- 2.2.2 Molecules containing specific IDRs
- 2.3 JNK activation and axon growth/regeneration
- 3 Perspectives
- Chapter 16. Phosphoproteomic and bioinformatic methods for analyzing axon growth and regeneration
- 1 Introduction
- 2 Phosphoproteomics of growth cone membrane (GCM) fraction
- 3 Mass spectrometry-based label-free quantitative phosphoproteomics and proteomics
- 4 High frequency of P-directed phosphosites in GCM fractions
- 5 GAP-43
- 6 In vivo assays for axon regeneration
- 7 Establishment of marker probes for axon regeneration
- 8 Prediction of activated protein kinases in axon growth or regeneration
- 9 Phosphorylation of GAP-43 in primates
- 10 Conclusion
- Section VI. Standardization approaches: Application of machine learning and artificial intelligence
- Chapter 17. Axon regeneration: Standardization of quantification using optic nerve as a system
- 1 Introduction
- 2 Questions pertaining to issues with current standardization
- 2.1 How do we optimize data for pressures utilized per animal in ONC procedures?
- 2.2 What role does inflammation play in ONC procedures, and how do we quantify the involvement?
- 2.3 Concerning the diameter diversity among various experimental lines and sexes of animals, do we have a need for an average optic nerve (ON) size standardized database?
- 2.4 Should researchers be recommended to measure and standardize glial scar intensity in various experimental mice after ONC?
- 2.5 Does the approximal distance from globe needs to be standardized?
- 2.6 Should the sterilization methods between surgical procedures be standardized?
- 3 Standardization approaches
- 4 Relevance to larger biological expansion of knowledge
- 5 Conclusion
- Section VII. Reconnectivity and new approaches
- Chapter 18. Subtype-specific reconnection of regenerated retinal ganglion cell axons: Lessons learned from mouse models
- 1 Introduction
- 2 Various RGC subtypes and axonal trajectories
- 2.1 ipRGC projections
- 2.2 Projections of direction-selective RGCs (DSRGCs) and other non-ipRGCs
- 3 Efforts toward building a retinal projectome
- 3.1 RGC subtypes and axon regeneration
- 3.2 RGC subtypes and target reinnervation
- 4 Conclusion and perspectives for future studies
- Chapter 19. Axon pathfinding, ipsi- and contralateral projections
- 1 Introduction
- 2 Spatial and temporal localization of ipsilateral and contralateral RGCs
- 3 Molecular insights into formation of ipsilateral and contralateral axon guidance
- 3.1 Generation and differentiation of ipsilateral and contralateral RGCs
- 3.2 Ipsilateral axon guidance mechanisms
- 3.3 Contralateral axon guidance mechanisms
- 3.4 Transcriptional control of retinal axon guidance
- 3.5 Retinogeniculate and retinocollicular axon projections
- 3.6 Retinal axon fasciculation
- 4 Regulation of retinal axon regeneration by factors relevant to retinal axon development
- 5 Future direction and questions
- Chapter 20. Axon guidance, genes, proteins and beyond
- 1 Introduction
- 2 Netrins
- 3 Semaphorins
- 4 Ephrins
- 5 Robo/Slits
- 6 Other guidance-like molecules and mechanisms to shape neuronal circuits
- 6.1 Morphogens
- 6.2 Proteoglycans
- 6.3 Lipids
- 6.4 Physical forces
- 7 Conclusions and perspectives
- Section VIII. Regeneration applicable in other fields
- Chapter 21. The use of stereological and electron microscopic techniques in the assessment of peripheral nerve regeneration success
- 1 Introduction: Basic principles of stereology
- 2 Preparation of the samples for transmission electron microscopy
- 2.1 Primary fixation
- 2.2 Secondary fixation
- 2.3 Dehydration step
- 2.4 Infiltration of the resin
- 3 Total volume estimation of the ganglion tissue (Cavalieri's principle)
- 4 Estimation of sensory neuron perikaryon volume
- 5 Stereological estimations in a cell or cell component on electron microscopic images
- 6 Estimation of the sensory neuron number in ganglion tissue: A combination of fractionator and disector techniques
- 7 The estimation of the total myelinated nerve fiber number, axon area, and myelin sheath thickness
- 8 Conclusion
- Chapter 22. Optic nerve as a regeneration model for spinal cord injury
- 1 Introduction
- 2 Anatomy and injury models
- 2.1 Optic nerve anatomy and injury models
- 2.2 Peripheral nerve anatomy and injury models
- 2.3 Spinal cord anatomy and injury models
- 3 Neuron-intrinsic mechanisms controlling axon growth and regeneration
- 3.1 Intrinsic regulators identified in peripheral nerve injury model
- 3.2 Intrinsic regulators identified in optic nerve injury model
- 4 Neuroinflammation
- 5 Gliosis and fibrosis after neural injury
- 6 Summary
- Chapter 23. Axon regeneration after spinal cord and brain injuries
- 1 Introduction
- 2 Axon regeneration after spinal cord injury
- 2.1 Major pathophysiology after SCI
- 2.2 Extrinsic factors to regulate CNS axon regrowth
- 2.2.1 Targeting astrogliosis
- 2.2.2 CSPGs and their receptors
- 2.2.3 CNS myelin inhibitors
- 2.2.4 Upregulation of repulsive axon guidance molecules
- 2.2.5 Lack of appropriate neurotrophic support
- 2.2.6 Convergent signals downstream of axon growth inhibitors
- 2.2.7 Synapse-mediated inhibition of axon regeneration
- 2.2.8 Glial reprogramming and microglia-associated genes
- 2.3 Intrinsic factors to control CNS axon regeneration
- 2.3.1 Intracellular signaling pathways. Multiple signaling pathways are highly active during neurodevelopment, but they are mainly downregulated and silenced to maintain the functional stability of adult CNS. Upregulating and/or activating some of these signals could promote the regeneration of CNS neurons
- 2.3.2 Transcriptional factors
- 2.3.3 Epigenetic regulators. Epigenetic factors regulate the transcription and expression of heritable DNAs by modifying DNAs and their wrapping histone proteins. Targeting some epigenetic regulators could promote axon regrowth and neural repair after SCI
- 2.3.4 Inflammation-related signals
- 2.3.5 Cytoskeleton dynamics and mitochondria transport
- 2.3.6 Temporary regrowth state of CST neurons in adult mice with SCI
- 2.4 Neuronal relays for neuroplasticity and functional recovery
- 2.4.1 Neuronal relay pathways
- 2.4.2 Rehabilitation and neuroplasticity
- 2.5 Promoting additional axon regeneration and recovery with combined approaches
- 2.5.1 Neurotrophins and transplants
- 2.5.2 Suppressing axon growth inhibitors combined with transplants
- 2.5.3 Targeting multiple genes to further enhance neuronal growth capacity
- 2.5.4 Molecular therapies combined with rehabilitation
- 2.6 Clinical trials of SCI to evaluate axon growth-promoting drugs
- 3 Axon regeneration after brain injuries
- 3.1 Axon regeneration after traumatic brain injury
- 3.1.1 Major pathophysiology after TBI
- 3.1.2 Axon regeneration after TBI
- 3.2 Axon regrowth after stroke
- 3.2.1 Major pathophysiology of stroke
- 3.2.2 Promoting axon regrowth after stroke
- 3.3 Axon regeneration after other types of brain damage
- 3.3.1 Axon regeneration in AD
- 3.3.2 Axon regeneration in MS
- 4 Conclusions and perspectives
- 4.1 Major recent progress
- 4.2 Top challenges
- 4.3 Perspectives
- Section IX. Regulatory approval processes and clinical relevant aspects
- Chapter 24. A primer on food and drug administration's approval process
- 1 Introduction
- 2 Regulatory oversight and organizational structure of FDA
- 3 Categorization, pathways, and adherence to regulations for ophthalmic products: Devices, pharmaceuticals, biologics, and combination products
- 3.1 Ophthalmic devices
- 3.2 Ophthalmic drugs
- 3.3 Ophthalmic biologics
- 3.4 Combination products (drug/device/biologic)
- 4 Regulations and contemporary practices in FDA approval for ophthalmic products
- 5 Applicant responsibilities and FDA approval process for ophthalmic products
- 5.1 Phase I: Safety and tolerability
- 5.2 Phase II: Efficacy and safety
- 5.3 Phase III: Large-scale efficacy assessment
- 6 Factors affecting FDA approval of ophthalmic products
- 7 Case analyses of FDA-approved ophthalmic products
- 7.1 Eylea (aflibercept) for age-related macular degeneration
- 7.2 Alphagan P (brimonidine) for glaucoma
- 7.3 Luxturna (voretigene neparvovec) for inherited retinal dystrophy
- 7.4 Raindrop Near Vision Inlay for presbyopia
- Authorship confirmation/contribution statement
- Conflict of interest
- Funding
- Abbreviations
- Chapter 25. Strategic approaches for antiglaucoma drug discovery—Successes and some failures
- 1 Introduction
- 2 New IOP-lowering drugs and miniature devices
- 2.1 Rho kinase inhibitors (ripasudil and netarsudil)
- 2.2 Conjugate of latanoprost and NO-donor (latanoprostene bunod)
- 2.3 Sustained delivery bimatoprost implant
- 2.4 Novel nonprostaglandin EP2-prostanoid receptor agonist (omidenepag isopropyl)
- 2.5 Development and approval of novel AQH drainage microshunts
- 3 Compounds whose development was halted (“failures”)
- 4 Conclusions and future prospects
- Section X. Protocols and miscellaneous topics
- Chapter 26. Optic nerve crush as a model system for axon regeneration studies
- 1 Introduction
- 2 Materials and equipment
- 3 Procedure
- 3.1 Optic nerve crush surgery
- 3.2 Intravitreal metabolite injection
- 3.3 Intravitreal CTB injection
- 3.4 Tissue dissection and optic nerve clearing
- 3.5 Retina flat mount dissection and immunostaining
- Chapter 27. Protocol for quantitative metabolomics analysis of axon regeneration samples
- 1 Introduction
- 2 Materials
- 2.1 Chemicals
- 2.2 Ultra high-performance liquid chromatography columns and vials
- 2.3 Ultra high-performance liquid chromatography and mass spectrometry instruments
- 3 Methods
- 3.1 Preparation of tissue samples
- 3.1.1 Dissection and extraction
- 3.1.2 Post extraction
- 3.1.3 Preparation of pooled quality control (QC) samples
- 3.2 Preparation of extraction blanks
- 3.3 Mobile phase preparation
- 3.3.1 Preparation of mobile phase A and B for reverse phase C18+ UHPLC positive and negative ion mode
- 3.3.2 Preparation of mobile phase A and B for HILIC UHPLC positive and negative ion mode
- 3.4 UHPLC and MS methods
- 3.4.1 Reversed phase C18+ UHPLC gradient
- 3.4.2 HILIC UHPLC gradient
- 3.4.3 HESI-II ion source settings
- 3.5 Sequence set-up
- 4 Bioinformatics
- 5 Notes
- Chapter 28. Retinal/optic nerve gene expression data analysis for nonbioinformaticians
- 1 Introduction
- 2 Gene expression analysis
- 3 Web-based analysis platforms
- 3.1 GEO2R
- 3.1.1 BioJupies
- 3.1.2 Galaxy
- 3.2 Quality controls and technical considerations for combining samples
- 3.3 Other useful tools
- 3.3.1 Metascape
- 3.3.2 Timer 2.0
- 3.3.3 GeneCards
- 4 Conclusion
- Chapter 29. Protocol for the comparison of RNA transcriptome between the optic nerve and spinal cord axonal regeneration in zebrafish
- 1 Introduction
- 1.1 Transcriptome
- 1.2 RNA transcriptomic study database
- 1.3 General RNA transcriptomic study design
- 1.4 Common statistical analysis (Chen & Wong, 2019)
- 1.5 Purpose of this protocol
- 2 Protocol
- 2.1 GEO database search https://www.ncbi.nlm.nih.gov/geo/info/qqtutorial.html, (Querying GEO DataSets, 2023)
- 2.2 Accession display page
- 2.3 Research article
- 2.3.1 Method section
- 2.3.2 Result section
- 3 Results
- 4 Significance
- Chapter 30. A comparison of axon regeneration in Xenopus and Danio rerio
- 1 Introduction
- 2 Methodology
- 3 Data analysis
- 4 Results
- 5 Discussion
- 6 Conclusion
- 7 Supplemental data
- Chapter 31. An overview of single-cell omics, spatial omics, and omics integration in axon regeneration
- 1 Single-cell omics approaches
- 1.1 RNA and microwell transcriptomic sequencing
- 1.2 Isobaric labeling and label-free workflows for single-cell proteome profiling
- 1.3 Sample preparation methods for processing low-input samples in single-cell proteomics
- 1.4 Mass spectrometry for single-cell proteomics
- 1.5 SCoPE-MS and SCoPE2 technologies for single-cell proteomics
- 1.6 Mass spectrometry for lipidomics and metabolomics
- 1.7 Single-cell omics application in axon regeneration
- 1.8 Transcriptomics analysis in axon regeneration
- 1.9 Proteomics analysis in axon regeneration
- 1.10 Lipidomics analysis in axon regeneration
- 1.11 Metabolomics analysis in axon regeneration
- 1.12 Summary remarks for single-cell omics
- 2 Spatial omics
- 2.1 In situ hybridization-based techniques
- 2.2 Spatial transcriptomics, slide-seq antibody-based multiplexed spatial proteomics
- 2.3 Imaging mass cytometry
- 2.4 Imaging mass spectrometry
- 3 Multi-omics integration
- 3.1 Currently available techniques and methodologies
- 3.2 Horizontal, vertical, and diagonal integration
- 3.3 Unsupervised data integration
- 3.4 Supervised data integration
- 3.5 Knowledge driven and data driven multi-omics integration
- 3.6 Multi-omics integration tools
- 3.7 Utilities and future directions
- Index
- Edition: 1
- Published: January 15, 2025
- Imprint: Academic Press
- No. of pages: 466
- Language: English
- Paperback ISBN: 9780443155802
- eBook ISBN: 9780443155819
SB
Sanjoy K. Bhattacharya
Sanjoy Bhattacharya is a tenured full Professor at the Department of Ophthalmology, University of Miami, with secondary appointments in biochemistry, molecular biology, neuroscience, cellular and molecular pharmacology programs. He earned his doctorate in Biochemical Engineering and Biotechnology. Dr. Bhattacharya’s laboratory, with its diverse expertise in engineering, computer programming, biology, and mass spectrometry, is dedicated to studying the complete set of molecules and biological systems involved in axon regeneration. He serves on the editorial board of several peer-reviewed journals including PLoS One as an academic editor, Experimental Eye Research as Special issues and Review editor, and Translational Metabolomics as the Editor in Chief. Professor Bhattacharya has held several leadership positions including Chair of the scientific advisory board of Malignancy Research Foundation and Chair of Miller School of Medicine Faculty Council. He is also the founding director of Miami Integrative Metabolomics Research Center.