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| # 🧑🤝🧑 Dependientes | ||
| Las siguientes aplicaciones se basan en *gget*: | ||
| - [Therapeutics Data Commons (TDC)](https://tdcommons.ai/) | ||
| Base de inteligencia artificial para la ciencia terapéutica ([código fuente](https://github.com/mims-harvard/TDC), [artículo en Nat Chem Bio](https://www.nature.com/articles/s41589-022-01131-2)) del laboratorio de Inteligencia Artificial para Medicina y Ciencia de Harvard. | ||
| - [BioDiscoveryAgent](https://github.com/snap-stanford/BioDiscoveryAgent) | ||
| BioDiscoveryAgent es un agente de IA basado en modelos de lenguaje para el diseño en bucle cerrado de experimentos de perturbación genética ([preprint](https://arxiv.org/abs/2405.17631)) del Proyecto de Análisis de Redes de Stanford. | ||
| - [DeepChopper](https://ylab-hi.github.io/DeepChopper/) | ||
| Modelos de lenguaje para identificar lecturas artificiales quiméricas en datos de secuenciación directa de ARN de NanoPore por el laboratorio de Yang en Northwestern. | ||
| - [BRAD](https://github.com/Jpickard1/BRAD) | ||
| Un chatbot impulsado por un modelo de lenguaje para bioinformática ([documentación](https://brad-bioinformatics-retrieval-augmented-data.readthedocs.io/en/latest/index.html), [página principal del proyecto](https://brad-bioinformatics-retrieval-augmented-data.readthedocs.io/_/downloads/en/latest/pdf/)). | ||
| - [scPRINT](https://www.jkobject.com/scPRINT/) | ||
| scPRINT es un modelo transformer grande diseñado para inferir redes génicas (conexiones entre genes que explican el perfil de expresión de la célula) a partir de datos de scRNAseq ([preprint](https://www.biorxiv.org/content/10.1101/2024.07.29.605556v1)). | ||
| - [AnoPrimer](https://sanjaynagi.github.io/AnoPrimer/landing-page.html): | ||
| AnoPrimer es un paquete de Python para el diseño de cebadores en *An. gambiae* y *An. funestus*, teniendo en cuenta la variación genética en especímenes de genomas completos secuenciados de la naturaleza en datos de malariagen. | ||
| - [AvaTaR](https://github.com/zou-group/avatar) | ||
| Optimización de Agentes de LLM para Recuperación de Conocimiento Asistida por Herramientas (NeurIPS 2024) por el laboratorio de James Zou en la Universidad de Stanford. | ||
| - [GRLDrugProp](https://github.com/Madscba/GRLDrugProp) | ||
| Aprendizaje de representación de grafos para modelar propiedades de fármacos. | ||
| - Implementación en Rust de gget: https://github.com/noamteyssier/ggetrs | ||
| - https://github.com/Superbio-ai/getbio | ||
| - https://github.com/yonniejon/AchillesPrediction | ||
| - https://github.com/ELELAB/cancermuts | ||
| - https://github.com/Benoitdw/SNPrimer | ||
| - https://github.com/louisjoecodes/a16z-hackathon-project | ||
| - https://github.com/EvX57/BACE1-Drug-Discovery | ||
| - https://github.com/vecerkovakaterina/hidden-genes-msc | ||
| - https://github.com/vecerkovakaterina/llm_bioinfo_agent | ||
| - https://github.com/greedjar74/upstage_AI_Lab | ||
| - https://github.com/alphavector/all | ||
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| Ver también: https://github.com/pachterlab/gget/network/dependents | ||
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| # 📃 Publicaciones destacadas | ||
| - David Bradley et al., [The fitness cost of spurious phosphorylation.](https://doi.org/10.1038/s44318-024-00200-7) *The EMBO Journal* (2024). DOI: 10.1038/s44318-024-00200-7 | ||
| - Mikael Nilsson et al., [Resolving thyroid lineage cell trajectories merging into a dual endocrine gland in mammals.](https://doi.org/10.21203/rs.3.rs-5278325/v1) *Nature Portfolio (en revisión)* (2024). DOI: 10.21203/rs.3.rs-5278325/v1 | ||
| - Avasthi P et al., [Repeat expansions associated with human disease are present in diverse organisms.](https://doi.org/10.57844/arcadia-e367-8b55) *Arcadia* (2024). DOI: 10.57844/arcadia-e367-8b55 | ||
| - Ibrahim Al Rayyes et al., [Single-Cell Transcriptomics Reveals the Molecular Logic Underlying Ca2+ Signaling Diversity in Human and Mouse Brain.](https://doi.org/10.1101/2024.04.26.591400) *bioRxiv* (2024). DOI: 10.1101/2024.04.26.591400 | ||
| - David R. Blair & Neil Risch. [Dissecting the Reduced Penetrance of Putative Loss-of-Function Variants in Population-Scale Biobanks.](https://doi.org/10.1101/2024.09.23.24314008) *medRxiv* (2024). DOI: 10.1101/2024.09.23.24314008 | ||
| - Shanmugampillai Jeyarajaguru Kabilan et al., [Molecular modelling approaches for the identification of potent Sodium-Glucose Cotransporter 2 inhibitors from Boerhavia diffusa for the potential treatment of chronic kidney disease.](https://doi.org/10.21203/rs.3.rs-4520611/v1) *Journal of Computer-Aided Molecular Design (en revisión)* (2024). DOI: 10.21203/rs.3.rs-4520611/v1 | ||
| - Joseph M Rich et al., [The impact of package selection and versioning on single-cell RNA-seq analysis.](https://pmc.ncbi.nlm.nih.gov/articles/PMC11014608/#:~:text=10.1101/2024.04.04.588111) *bioRxiv* (2024). DOI: 10.1101/2024.04.04.588111 | ||
| - Sanjay C. Nagi et al., [AnoPrimer: Primer Design in malaria vectors informed by range-wide genomic variation.](https://wellcomeopenresearch.org/articles/9-255/v1) *Wellcome Open Research* (2024). | ||
| - Yasmin Makki Mohialden et al., [A survey of the most recent Python packages for use in biology.](http://dx.doi.org/10.48047/NQ.2023.21.2.NQ23029) *NeuroQuantology* (2023). DOI: 10.48047/NQ.2023.21.2.NQ23029 | ||
| - Kimberly Siletti et al., [Transcriptomic diversity of cell types across the adult human brain.](https://doi.org/10.1126/science.add7046) *Science* (2023). DOI: 10.1126/science.add7046 | ||
| - Beatriz Beamud et al., [Genetic determinants of host tropism in Klebsiella phages.](https://doi.org/10.1016/j.celrep.2023.112048) *Cell Reports* (2023). DOI: 10.1016/j.celrep.2023.112048 | ||
| - Nicola A. Kearns et al., [Generation and molecular characterization of human pluripotent stem cell-derived pharyngeal foregut endoderm.](https://doi.org/10.1016/j.devcel.2023.08.024) *Cell Reports* (2023). DOI: 10.1016/j.devcel.2023.08.024 | ||
| - Jonathan Rosenski et al., [Predicting gene knockout effects from expression data.](https://link.springer.com/article/10.1186/s12920-023-01446-6) *BMC Medical Genomics* (2023). DOI: 10.1186/s12920-023-01446-6 | ||
| - Peter Overby et al., [Pharmacological or genetic inhibition of Scn9a protects beta-cells while reducing insulin secretion in type 1 diabetes.](https://doi.org/10.1101/2023.06.11.544521) *bioRxiv* (2023). DOI: 10.1101/2023.06.11.544521 | ||
| - Mingze Dong et al., [Deep identifiable modeling of single-cell atlases enables zero-shot query of cellular states.](https://doi.org/10.1101/2023.11.11.566161) *bioRxiv* (2023). DOI: 10.1101/2023.11.11.566161 | ||
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| # 📰 Noticias | ||
| - Documental corto sobre *gget*: https://youtu.be/cVR0k6Mt97o | ||
| - Episodio de podcast para el Prototype Fund Public Interest Podcast sobre la importancia del software de código abierto y su papel en la investigación académica (en alemán): https://public-interest-podcast.podigee.io/33-pips4e4 | ||
| - Anuncio del Prototype Fund: https://prototypefund.de/project/gget-genomische-datenbanken/ |