1. Leveraging Disease Association Degree for High-Accuracy MicroRNA Target Prediction

    This article has 1 author:
    1. Baiming Chen
    This article has been curated by 1 group:
    • Curated by eLife

      eLife Assessment

      This valuable study introduces miRTarDS, a novel computational framework that predicts microRNA-target interactions based on a publicly available pretrained Sentence-BERT language model and downstream classification analysis. The strength of the evidence is incomplete, as the evaluation framework relies on unreliable ground-truth and false sets. Furthermore, the analysis fails to compare miRTarDS against existing state-of-the-art biomedical language models.

    Reviewed by eLife

    This article has 4 evaluationsAppears in 1 listLatest version Latest activity
  2. Federated Knowledge Retrieval Elevates Large Language Model Performance on Biomedical Benchmarks

    This article has 2 authors:
    1. Janet Joy
    2. Andrew I. Su

    Reviewed by GigaScience

    This article has 2 evaluationsAppears in 1 listLatest version Latest activity
  3. SpaceBF: Spatial coexpression analysis using Bayesian Fused approaches in spatial omics datasets

    This article has 2 authors:
    1. Souvik Seal
    2. Brian Neelon

    Reviewed by GigaScience

    This article has 2 evaluationsAppears in 1 listLatest version Latest activity
  4. nf-core/proteinfamilies: A scalable pipeline for the generation of protein families

    This article has 13 authors:
    1. Evangelos Karatzas
    2. Martin Beracochea
    3. Fotis A. Baltoumas
    4. Eleni Aplakidou
    5. Lorna Richardson
    6. James A. Fellows Yates
    7. Daniel Lundin
    8. nf-core community
    9. Aydin Buluç
    10. Nikos C. Kyrpides
    11. Ilias Georgakopoulos-Soares
    12. Georgios A. Pavlopoulos
    13. Robert D. Finn

    Reviewed by GigaScience

    This article has 2 evaluationsAppears in 1 listLatest version Latest activity
  5. The Hok bacterial toxin: diversity, toxicity, distribution and genomic localization

    This article has 8 authors:
    1. Andrés Escalera-Maurer
    2. Adriana Messineo
    3. Thibaud T. Renault
    4. Elena Nicollin
    5. Erika Castaneda-Sastre
    6. Matthieu Brunot
    7. Cléo Berrehail
    8. Anaïs Le Rhun

    Reviewed by Review Commons

    This article has 4 evaluationsAppears in 1 listLatest version Latest activity
  6. Interpreting the Effects of DNA Polymerase Variants at the Structural Level Using MAVISp and Molecular Dynamics Simulations

    This article has 8 authors:
    1. Matteo Arnaudi
    2. Karolina Krzesińska
    3. Ludovica Beltrame
    4. Pablo Sánchez-Izquierdo Besora
    5. Matteo Tiberti
    6. Mef Nilbert
    7. Anna Rohlin
    8. Elena Papaleo

    Reviewed by Review Commons

    This article has 4 evaluationsAppears in 1 listLatest version Latest activity
  7. A genotype-phenotype transformer to assess and explain polygenic risk

    This article has 7 authors:
    1. Ingoo Lee
    2. Zachary S. Wallace
    3. Yuqi Wang
    4. Sungjoon Park
    5. Hojung Nam
    6. Amit R. Majithia
    7. Trey Ideker

    Reviewed by Review Commons

    This article has 4 evaluationsAppears in 1 listLatest version Latest activity
  8. Comparative evaluation of computational methods for reconstruction of human viral genomes

    This article has 7 authors:
    1. Maria J. P. Sousa
    2. Mari Toppinen
    3. Lari Pyöriä
    4. Klaus Hedman
    5. Antti Sajantila
    6. Maria F. Perdomo
    7. Diogo Pratas

    Reviewed by GigaScience

    This article has 3 evaluationsAppears in 1 listLatest version Latest activity
  9. An Integrative Multi-Omics Random Forest Framework for Robust Biomarker Discovery

    This article has 5 authors:
    1. Wei Zhang
    2. Hanchen Huang
    3. Lily Wang
    4. Brian D. Lehmann
    5. Steven X. Chen

    Reviewed by GigaScience

    This article has 3 evaluationsAppears in 1 listLatest version Latest activity
  10. Squidly: Enzyme Catalytic Residue Prediction Harnessing a Biology-Informed Contrastive Learning Framework

    This article has 4 authors:
    1. William JF Rieger
    2. Mikael Boden
    3. Frances Arnold
    4. Ariane Mora
    This article has been curated by 1 group:
    • Curated by eLife

      eLife Assessment

      This important contribution to enzyme annotation offers a deep learning framework for catalytic site prediction. Integrating biochemical knowledge with large language models, the authors demonstrate how to extract meaningful information from sequence alone. They introduce Squidly, a freely available new ML modeling framework, that outperforms existing tools on standard benchmarks, including the CataloDB dataset. The evidence is convincing, with an extensively and carefully addressed narrative upon revision.

    Reviewed by eLife

    This article has 7 evaluationsAppears in 1 listLatest version Latest activity
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