Pathway: Biyolojik Mekanizmalar ve Hücresel Süreçler

The verified archive summary: Technical parameters compiled from the Reactome Pathway Knowledgebase official open data archive.
Official source institution: Reactome Pathway Knowledgebase
Provenance: Reactome Pathway Knowledgebase Archive
Verified parameters: Verified open data and peer-reviewed catalog records

So this is about the Reactome Pathway Knowledgebase – a well-known bioinformatics database. Let me think about what’s actually known about Reactome.

Reactome is a curated, open-source database of human biology and medicine pathways. It’s one of the most important resources in molecular biology and systems biology. Let me recall what I actually know about Reactome:

1. Reactome was originally developed at the Wellcome Trust Sanger Institute. It started around 2003-2005 as a human pathway database.

2. It’s now part of the Open Targets initiative (along with other resources). Actually, Reactome is now hosted by the European Molecular Biology Laboratory’s European Bioinformatics Institute (EMBL-EBI).

3. Reactome contains manually curated, peer-reviewed pathways. Each reaction/pathway is backed by scientific literature references.

4. It covers human biology but has expanded to orthologous pathways across many species (over 100 species now).

5. Key features:
– Pathway viewer (visual representation)
– 3D structures integration
– Reaction data
– Molecular function, cellular component annotations
– The Reactome Graph Database (RGD)
– ReactomeJL Java library
– REST API
– BioPAX and SBML export formats
– Human Protein Atlas integration
– The concept of “disease” associations

6. Reactome uses a hierarchical structure – reactions are nested within pathways, which are nested within higher-level processes.

7. It’s used for functional profiling, pathway enrichment analysis (very popular in genomics/transcriptomics studies).

8. Reactome’s data model includes entities like: Entity, PhysicalEntity, MolecularEntity, SimpleEntity, Complex, ProteinWithBindingSites, etc.

9. The database is updated regularly and versioned.

10. It integrates with other resources like UniProt, Gene Ontology, etc.

Now, the scrap is somewhat abstract – it’s metadata about a “Pathway: Biological Mechanisms and Cellular Processes” category. The focus is on biochemical pathways and signaling.

What’s NOT in the scrap:
– No specific pathway named
– No specific molecular mechanism detailed
– No specific drug/pharmacokinetic data
– No specific 3D protein structure

1. Something about Reactome’s origins and curation philosophy – the human effort behind the data
2. Something about the data model – how molecular reality is translated into structured data
3. Something about pathway enrichment and how researchers use it
4. Something about the integration of 3D structures and the spatial dimension
5. Something about open science and the ecosystem

Let me write this in Turkish, flowing prose, with HTML tags only.

Opening paragraph: Hook about the cell as a city of molecular traffic, and how Reactome maps this. The bridge between the wet lab and the digital.

Section 1 (after opening, before INLINE_IMAGE_1): The nature of Reactome – what it is, its origins at Sanger Institute, the curation philosophy. “İnsan eliyle yazılmış bir hücre haritası” or similar.

Section 2: The data model – how molecular entities are structured, the ontology, the hierarchy. “Moleküler gerçeğin kodu” or similar.

Section 3: The application – pathway enrichment, how genomics studies use it, the integration with 3D structures and disease.

Section 4: Open science, the ecosystem, the future.

Let me be careful about accuracy. Let me recall facts about Reactome:

– Reactome began development at the Wellcome Trust Sanger Institute (Cambridge, UK). The initial publication was Pubault et al. 2005 “Reactome: a knowledgebase of signaling pathways” in Nucleic Acids Research.
– The major reference paper: Jassal et al. 2020 “The Reactome pathway knowledgebase” in Nucleic Acids Research.
– It’s now part of Open Targets and hosted at EMBL-EBI.
– The database is manually curated by scientists.
– Each data item has literature references.
– It covers human pathways and orthologs across species.
– Currently over 100 species (I think it’s around 130+ species now).
– Reactome Graph Database (RGD) – a graph database version.
– BioPAX (Biological Pathway Exchange) format for export – Reactome is a major contributor to BioPAX standard.
– SBML (Systems Biology Markup Language) export.
– The Reactome API (REST and GraphQL).
– ReactomeJL – Java library.
– The pathway viewer uses the Reactome SVG viewer.
– Functional profiling / pathway enrichment analysis is a core application.
– Integration with Human Protein Atlas, GTEx, etc.
– The concept of “Entity” in the data model.
– Disease annotations.

Let me be careful not to overstate. I’ll say it started at Sanger, it’s now at EMBL-EBI, it’s part of Open Targets.

Actually, let me reconsider the Open Targets connection. Reactome is one of the data sources for OpenTargets. OpenTargets combines data from many sources including Reactome, Open Targets Genetics, etc. Yes.

Let me also recall: Reactome provides “Pathway Insights” tool for enrichment analysis. The “Pathway Insights 3” tool.

The data model: Reactome uses OWL (Web Ontology Language) to define its ontology. Entities include PhysicalEntity, MolecularEntity, SimpleEntity, Complex, Polymer, etc.

Let me write a compelling piece.

I need to place after the second section and after the third section.

Wait, let me re-read: “İkinci bölümün sonrasına , üçüncü bölümün sonrasına yerleştir.”

So after the second section (the second

section), place INLINE_IMAGE_1. After the third section, place INLINE_IMAGE_2.

So the structure:
– Opening paragraph (no heading, or is the opening part of section 1?)
– Actually, let me think. The opening paragraph is the first paragraph. Then sections with h2 headings.

Let me interpret: The “bölüm” (section) refers to the h2 sections. So:
– Opening paragraph
– Section 1 (h2)
– Section 2 (h2) … after this, INLINE_IMAGE_1
– Section 3 (h2) … after this, INLINE_IMAGE_2
– Section 4 (h2)

Hmm, but the opening paragraph – is it before any heading? Let me structure it as:

Opening paragraph

Section 1 title

Section 1 content

Section 2 title

Section 2 content

Section 3 title

Section 3 content

Section 4 title

Section 4 content

That works. Let me make 4 sections. Actually the instruction says 3-5 subheadings. Let me do 4.

Let me draft the Turkish content.

Opening paragraph:
The cell is a metropolis where millions of molecular conversations happen every second. Proteins find each other in the crowded cytoplasm, enzymes pass chemical messages along relay lines, signaling cascades amplify a single signal into a cellular decision. For decades, biologists studied these processes one molecule at a time. Then came the ambition to map the whole – to capture the complete choreography of life’s molecular traffic in a single, queryable, open archive. That archive is Reactome.

Let me write this in beautiful Turkish.

“Hücre, her saniye milyonlarca moleküler sohbetin yaşandığı bir metropolüdür.”

Let me continue drafting.

Section 1 title: “Sanger’dan doğan bir fikrin hikayesi” – about origins and curation philosophy.

Content: Reactome’s origin at the Wellcome Trust Sanger Institute, the initial 2005 publication, the philosophy of manual curation – that each reaction is written by scientists who read the literature, not generated by algorithms. The distinction between automated annotation and human-curated knowledge. The peer-reviewed nature.

Section 2 title: “Moleküler gerçeğin iskeleti: veri modeli” – about the data model.

Content: How Reactome represents molecular reality – the ontology, entities, the hierarchy of pathways nested within processes. The concept of PhysicalEntity, Complex, the reaction model. The use of BioPAX standard. The rigorous structure that lets a reaction be both a data point and a node in a network.

Section 3 title: “Genomun gürültüsünden anlam: zenginlik analizi” – about pathway enrichment and applications.

Content: How researchers use Reactome – the “Pathway Insights” enrichment analysis. Taking a list of genes from a sequencing experiment and finding which pathways are overrepresented. The integration of 3D protein structures, disease associations. The spatial dimension.

Section 4 title: “Açık veri, küresel ekosistem” – about open science.

Content: The open data philosophy, the REST API, ReactomeJL, the graph database, integration with OpenTargets and other resources. The versioning and regular updates. How open data accelerates discovery.

Let me write the full piece now with beautiful Turkish prose.

Let me make sure all terms are in Turkish but scientific terms can remain (they’re universally used). Actually the instruction says “Başlıklar ve terimler İSTİSNASIZ %100 TÜRKÇE olacaktır.” – Headings and terms will be 100% Turkish. Hmm, but scientific terms like “Reactome”, “BioPAX”, “UniProt” are proper nouns. I think the intent is that the prose and headings should be in Turkish, not that I need to translate proper scientific names. Let me use Turkish for the general language and keep proper nouns and universally-used scientific terms where appropriate. Actually, let me be careful – “terimler” (terms) 100% Turkish. I’ll translate common terms like “hücre”, “protein”, “enzim”, “sinyal”, “yolak” (pathway), “kinetik” etc. For proper nouns like Reactome, BioPAX, I’ll keep them as they are scientific identifiers. This is the reasonable interpretation.

Let me write.

Actually, let me reconsider the number of sections and where images go. Let me do 4 sections.

Let me write the prose now.

Draft:

Opening:
Hücre, her geçen saniye milyonlarca moleküler konuşmanın yaşandığı çılgın bir metropolüdür. Sitoplazmada sıkışık bir kalabalık içinden proteinler birbirini tanır, enzimler kimyasal mesajları bir şelalenin basamakları gibi aktarır, sinyal kaskadları tek bir molekülün fısıltısını hücrenin tamamının vereceği bir karara dönüştürür. Yü