Dataset Card for escher-human-edit

Human Edit dataset

  Dataset Structure





  Data Instances

Each instance contains:

source_image: The original image edited_image: The edited version of the image edit_instruction: The instruction used to edit the image source_image_caption: Caption for the source image target_image_caption: Caption for the edited image Additional metadata fields

  Data Splits

{}

Human post-edited test sentences for the WMT 2017 Automatic post-editing task. This consists in 2,000 English sentences belonging to the IT domain and already tokenized. Source and target segments can be downloaded from: https://lindat.mff.cuni.cz/repository/xmlui/handle/11372/LRT-2132. All data is provided by the EU project QT21 (http://www.qt21.eu/).

The WikiPrefs dataset is a human preferences dataset for Large Language Models alignment. It was built using the EditPrefs method from historical edits of Wikipedia featured articles

WikiAtomicEdits is a corpus of 43 million atomic edits across 8 languages. These edits are mined from Wikipedia edit history and consist of instances in which a human editor has inserted a single contiguous phrase into, or deleted a single contiguous phrase from, an existing sentence.

The Gene-Editing Tools For Non-Human Primates Market report segments the industry into By Technology (CRISPR/Cas9, Transcription Activator-Like Effectror Nucleases (TALENs), Zinc Finger Nucleases (ZFNs), Others), By Application (Biomedical Research, Transgenic Model Development, Pharmaceutical Development, Gene Therapy Research), By End User (Research Institutions, and more), and Geography.

Dataset Card for HQ-EDIT

HQ-Edit, a high-quality instruction-based image editing dataset with total 197,350 edits. Unlike prior approaches relying on attribute guidance or human feedback on building datasets, we devise a scalable data collection pipeline leveraging advanced foundation models, namely GPT-4V and DALL-E 3. HQ-Edit’s high-resolution images, rich in detail and accompanied by comprehensive editing prompts, substantially enhance the capabilities of existing image editing… See the full description on the dataset page: https://huggingface.co/datasets/UCSC-VLAA/HQ-Edit.

Human post-edited and reference test sentences for the En-De PBSMT WMT 2018 Automatic post-editing task. This consists of 2,000 German sentences for each file belonging to the IT domain and already tokenized. All data is provided by the EU project QT21 (http://www.qt21.eu/).

This page hosts downloadable data related to RE-Aging: A Functional Analysis Platform for Human RNA Editing Associated with Aging.

AIdata.zip: Contains detailed information on all A-to-I RNA editing sites.
CUdata.zip: Includes comprehensive data on all C-to-U RNA editing sites.
data_all.zip: Provides a complete dataset of all RNA editing sites across both A-to-I and C-to-U types.
cor.zip: Contains information on the relationship between editing levels of A-to-I sites in various organs and age.
sample_info.zip: Includes the corresponding GTEx Sample Information, essential for contextualizing the data.

Median fluorescent intensity (MFI) after Cas9 inhibition.

SEED-Data-Edit

SEED-Data-Edit is a hybrid dataset for instruction-guided image editing with a total of 3.7 image editing pairs, which comprises three distinct types of data: Part-1: Large-scale high-quality editing data produced by automated pipelines (3.5M editing pairs). Part-2: Real-world scenario data collected from the internet (52K editing pairs). Part-3: High-precision multi-turn editing data annotated by humans (95K editing pairs, 21K multi-turn rounds with a maximum… See the full description on the dataset page: https://huggingface.co/datasets/AILab-CVC/SEED-Data-Edit-Part1-Unsplash.

The human evaluation (HE) dataset created for English to German (EnDe) and English to French (EnFr) MT tasks was a subset of one of the official test sets of the IWSLT 2016 evaluation campaign. The resulting HE sets are composed of 600 segments for both EnDe and EnFr, each corresponding to around 10,000 words. Human evaluation was based on Post-Editing, i.e. the manual correction of the MT system output, which was carried out by professional translators. Nine and five primary runs submitted to the evaluation campaign were post-edited for the two tasks, respectively.

Data are publicly available through the WIT3 website wit3.fbk.eu. 600 segments for both EnDe and EnFr (10K tokens each). Respectively, 9 and 5 different automatic translations post-edited by professional translators (for Analysis of MT quality and Quality Estimation components).

Dataset Summary

Corpus of post-edited llm answers to accounting questions. We provide human edits with associated edit time, but also synthetic (LLM) edits following various scenarios.

  How to Use

from datasets import load_dataset

human_edits = load_dataset("Tiime/fr-qa-accounting-edits", name="human_edits")

synthetic_edits = load_dataset("Tiime/fr-qa-accounting-edits", name="synthetic_edits")

  Citation

If you use our dataset, please cite us at:… See the full description on the dataset page: https://huggingface.co/datasets/Tiime/fr-qa-accounting-edits.

As per Cognitive Market Research's latest published report, the Global Gene Editing Service market size was $6.21 Billion in 2022 and it is forecasted to reach $18.77 Billion by 2030. Gene Editing Service Industry's Compound Annual Growth Rate will be 14.9% from 2023 to 2030. Factors Impacting on Gene Editing Service Market

The rising demand for gene therapy drives the Gene Editing Service Market growth

Gene therapy has marked its significant importance in the field of medication over the last few decades. Gene therapy is used for the treatment associated with the genetic disorder. The data from the National Human Genome Research Institute (2018) states that approx. 350 million people across the globe are living with rare disorders and fewer than 200,000 people are diagnosed with this condition. About 80 % of these rare disorders are genetic in origin. With technological advancement gene therapy has grown as a most considered option for the treatment and control of several life-threatening diseases. such as hemophilia. The data from US Centers for Disease Control and Prevention states the presence of around 30,000 – 33,000 people with hemophilia in the US. This raises the demand for the gene editing services market.

Challenges for the Gene Editing Service Market

High expenses related to gene editing can hamper the growth of the gene editing service market growth. (Access Detailed Analysis in the Full Report Version)

Rising R&D activities will boost the Gene Editing Service market growth

Gene editing is being explored in a varied array of diseases, including single-gene rare disorders such as sickle cell disease and hemophilia. The number of venture capital (VC) agreements for firms exploring gene editing technology has surged dramatically since 2012. According to GlobalData's Pharma Intelligence Center, the number of VC agreements climbed from one in 2012 to 29 in 2021, with the total value of VC deals reaching more than $3.2 billion since 2012. Over $1.3 billion was raised in 2021 alone, more than 250% higher than in 2020 ($500 million). This investment is expected to propel the growth of the market. What is Gene Editing?

Gene editing is also called genome editing. It is a group of technologies that permit researchers to make a change in the DNA of organisms. Currently, there are several approaches are being developed for gene editing. One of the popular gene editing technologies is the CRISPR-Cas9 system. These technologies enable the addition, elimination, or alteration of genetic information at precise locations in the genome.

Jupyter notebook and supplemental datasets required to create critical figures for the publication.

Updated to include code for base-level and ClinVar analsis (R scripts)

Click to add a brief description of the dataset (Markdown and LaTeX enabled).

Provide:

a high-level explanation of the dataset characteristics explain motivations and summary of its content potential use cases of the dataset

Median fluorescent intensity (MFI) of B2M gRNA transfected cells.

Median fluorescent intensity (MFI) of GGTA1 gRNA transfected cells.

The Gene-Editing Tools For Non-Human Primates report features an extensive regional analysis, identifying market penetration levels across major geographic areas. It highlights regional growth trends and opportunities, allowing businesses to tailor their market entry strategies and maximize growth in specific regions.

According to Cognitive Market Research, the global Gene Editing market size will be USD 6.0 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 15.1% from 2024 to 2031. Market Dynamics of Gene Editing Market

Key Drivers for Gene Editing Market

Rising Demand for Therapeutic Applications - Gene editing holds promise for treating genetic disorders and complex diseases that were previously considered untreatable. Therapeutic applications of gene editing, particularly in somatic cell therapy and ex vivo editing of patient cells, offer potential cures or significant improvements in conditions such as cancer, genetic disorders, and infectious diseases. The ability to precisely correct disease-causing mutations at the genetic level presents a transformative approach to personalized medicine. Increasing investments from biotechnology and pharmaceutical companies, coupled with regulatory support for clinical trials and commercialization, accelerate the translation of gene editing technologies from the lab to clinical applications.
The increasing applications in agriculture and food security are anticipated to drive the Gene Editing market's expansion in the years ahead.

Key Restraints for Gene Editing Market

The potential unintended genetic changes and safety uncertainties hinder widespread acceptance and application of gene editing techniques and limit the Gene Editing industry growth.
The market also faces significant difficulties related to ethical and regulatory concerns.

Introduction of the Gene Editing Market

The Gene Editing market is at the forefront of biotechnological innovation, revolutionizing genetic research, agriculture, and therapeutic applications. Gene editing technologies, such as CRISPR-Cas9, enable precise modifications to DNA sequences, offering unprecedented capabilities to address genetic disorders, enhance crop traits, and develop novel therapeutics. This transformative potential has sparked immense interest across scientific communities and industries globally. However, the market faces significant challenges, including ethical considerations surrounding human germline editing, regulatory complexities, and concerns over off-target effects and safety. Despite these hurdles, ongoing advancements in gene editing tools, improved accuracy, and expanded applications in personalized medicine and sustainable agriculture are driving market growth. The increasing investment in biotechnology research and development, coupled with growing public awareness and acceptance of gene editing's potential benefits, positions the Gene Editing market as a pivotal force in shaping the future of healthcare, agriculture, and biotechnology industries worldwide.

Introduction

The Global Genome Editing Market is projected to grow from USD 9.4 billion in 2024 to approximately USD 44.4 billion by 2034. This represents a robust compound annual growth rate (CAGR) of 16.8% during the forecast period from 2025 to 2034. The market is being driven by rapid advancements in gene editing technologies, increasing demand for personalized medicine, and rising investment from public and private sectors. These developments are also supported by various initiatives from global health organizations and governments, aiming to advance research while maintaining ethical standards.

Technological innovation is a core driver of this market. Tools such as CRISPR-Cas9 have transformed the ability to modify DNA with high precision. These technologies enable scientists to correct genetic defects and explore gene function more efficiently. Their precision and low cost make them widely accessible across research institutions. The World Health Organization (WHO) has emphasized the importance of ensuring safe and ethical use, advocating for improved global capacity and system-level governance in gene editing.

In healthcare, genome editing is emerging as a powerful solution for treating genetic disorders and cancers. CRISPR is being explored for curing diseases such as sickle cell anemia and certain types of leukemia. These therapies offer hope for permanent treatment solutions rather than symptom management. Personalized medicine is another growing application, where patient-specific genetic profiles help develop targeted therapies. WHO guidelines focus on balancing medical advancement with ethical responsibility in this sector.

The applications of genome editing go beyond human health. In agriculture, it is used to enhance crop traits such as disease resistance, drought tolerance, and nutritional value. These improvements support global food security and environmental sustainability. In industrial biotechnology, gene editing contributes to the development of biofuels and biodegradable materials. These applications align with global efforts to reduce dependence on fossil fuels and minimize environmental impact.

Regulatory frameworks and institutional support are critical to this market’s growth. Projects like the UK’s 100,000 Genomes Project show how governments are integrating genome data into healthcare to improve diagnosis and treatment. WHO has called for global governance systems to oversee genome editing practices. These systems are designed to promote transparency, prevent misuse, and ensure equitable access to benefits. Continued collaboration between scientists, regulatory bodies, and health organizations will be vital to managing risks while supporting innovation.