1. Drug combination prediction for cancer treatment using disease-specific drug response profiles and single-cell transcriptional signatures

    This article has 5 authors:
    1. Daniel Osorio
    2. Parastoo Shahrouzi
    3. Xavier Tekpli
    4. Vessela N Kristensen
    5. Marieke L Kuijjer
    This article has been curated by 1 group:
    • Curated by eLife

      eLife Assessment

      The study conducted by Hurtado et al. offers important insights and solid evidence regarding the prediction of drug combinations for cancer treatment. By leveraging disease-specific drug response profiles and single-cell transcriptional signatures, this research not only demonstrates a novel and effective approach to identifying potential drug synergies but it also enhances our understanding of the underlying mechanisms of drug response prediction.

    Reviewed by eLife

    This article has 8 evaluationsAppears in 1 listLatest version Latest activity
  2. A comprehensive antigen-antibody complex database unlocking insights into interaction interface

    This article has 8 authors:
    1. Yuwei Zhou
    2. Wenwen Liu
    3. Ziru Huang
    4. Yushu Gou
    5. Siqi Liu
    6. Lixu Jiang
    7. Yue Yang
    8. Jian Huang
    This article has been curated by 1 group:
    • Curated by eLife

      eLife Assessment

      This useful manuscript provides a newly curated database (termed AACDB) of antibody-antigens structural information, alongside annotations that are either taken and from the PDB, or added de-novo. Sequences, structures, and annotations can be easily downloaded from the AACDB website, speeding up the development of structure-based algorithms and analysis pipelines to characterize antibody-antigen interactions. The methodology presented for this data curation is solid. The curated dataset will be of broad interest and value to researchers interested in antibody-antigen interactions.

    Reviewed by eLife

    This article has 8 evaluationsAppears in 1 listLatest version Latest activity
  3. Identification and classification of ion-channels across the tree of life: Insights into understudied CALHM channels

    This article has 10 authors:
    1. Rahil Taujale
    2. Sung Jin Park
    3. Nathan Gravel
    4. Saber Soleymani
    5. Rayna Carter
    6. Kennady Boyd
    7. Sarah Keuning
    8. Zheng Ruan
    9. Wei Lü
    10. Natarajan Kannan
    This article has been curated by 1 group:
    • Curated by eLife

      eLife Assessment

      The first part of this manuscript describes an interdisciplinary approach to mine the human channelome and discover further ion channel orthologues across diverse organisms. Although the findings and data curation enabled by the new approach are valuable to the ion channel community, as well as to those interested in improved methods for mining sequence space for their protein of interest, this part of the work is incomplete because critical methodological information is missing. Further validation of the improvements this approach shows over others is needed. The second part of the manuscript utilizes the approach described in the first part to delineate co-conserved amino acid patterns in CALHM channels, but the evidence provided to support the role of the identified residues in channel gating is currently inadequate.

    Reviewed by eLife

    This article has 3 evaluationsAppears in 1 listLatest version Latest activity
  4. RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species

    This article has 23 authors:
    1. David Kainer
    2. Matthew Lane
    3. Kyle A Sullivan
    4. J Izaak Miller
    5. Mikaela Cashman
    6. Mallory Morgan
    7. Ashley Cliff
    8. Jonathon Romero
    9. Angelica Walker
    10. D Dakota Blair
    11. Hari Chhetri
    12. Yongqin Wang
    13. Mirko Pavicic
    14. Anna Furches
    15. Jaclyn Noshay
    16. Meghan Drake
    17. A J Ireland
    18. Ali Missaoui
    19. Yun Kang
    20. John C Sedbrook
    21. Paramvir Dehal
    22. Shane Canon
    23. Daniel Jacobson

    Reviewed by GigaScience

    This article has 1 evaluationAppears in 1 listLatest version Latest activity
  5. Defining the limits of plant chemical space: challenges and estimations

    This article has 10 authors:
    1. Chloe Engler Hart
    2. Yojana Gadiya
    3. Tobias Kind
    4. Christoph A. Krettler
    5. Matthew Gaetz
    6. Biswapriya B. Misra
    7. David Healey
    8. August Allen
    9. Viswa Colluru
    10. Daniel Domingo-Fernández

    Reviewed by GigaScience

    This article has 2 evaluationsAppears in 1 listLatest version Latest activity
  6. V-pipe 3.0: a sustainable pipeline for within-sample viral genetic diversity estimation

    This article has 19 authors:
    1. Lara Fuhrmann
    2. Kim Philipp Jablonski
    3. Ivan Topolsky
    4. Aashil A Batavia
    5. Nico Borgsmüller
    6. Pelin Icer Baykal
    7. Matteo Carrara
    8. Chaoran Chen
    9. Arthur Dondi
    10. Monica Dragan
    11. David Dreifuss
    12. Anika John
    13. Benjamin Langer
    14. Michal Okoniewski
    15. Louis du Plessis
    16. Uwe Schmitt
    17. Franziska Singer
    18. Tanja Stadler
    19. Niko Beerenwinkel

    Reviewed by GigaScience

    This article has 2 evaluationsAppears in 1 listLatest version Latest activity
  7. Network-based anomaly detection algorithm reveals proteins with major roles in human tissues

    This article has 4 authors:
    1. Dima Kagan
    2. Juman Jubran
    3. Esti Yeger-Lotem
    4. Michael Fire

    Reviewed by GigaScience

    This article has 2 evaluationsAppears in 1 listLatest version Latest activity
  8. Steamboat: Attention-based multiscale delineation of cellular interactions in tissues

    This article has 4 authors:
    1. Shaoheng Liang
    2. Junjie Tang
    3. Guanghan Wang
    4. Jian Ma

    Reviewed by preLights

    This article has 1 evaluationAppears in 1 listLatest version Latest activity
  9. Unsupervised Representation Learning of C. elegans Poses and Behavior Sequences From Microscope Video Recordings

    This article has 2 authors:
    1. Maurice Deserno
    2. Katarzyna Bozek
    This article has been curated by 1 group:
    • Curated by eLife

      eLife Assessment

      This valuable study introduces a self-supervised machine learning method to classify C. elegans postures and behaviors directly from video data, offering an alternative to the skeleton-based approaches that rely on often error-prone tracking. This novel approach holds promise for advancing ethology research. That said, the strength of evidence is currently incomplete, as key aspects - including measuring head-tail orientation, increased behavioral interpretability, and quantitative comparisons to established methods - are underdeveloped and would benefit from further validation.

    Reviewed by eLife

    This article has 5 evaluationsAppears in 1 listLatest version Latest activity
  10. Artificial intelligence driven tumor risk stratification from single-cell transcriptomics using phenotype algebra

    This article has 17 authors:
    1. Namrata Bhattacharya
    2. Anja Rockstroh
    3. Sanket Suhas Deshpande
    4. Sam Koshy Thomas
    5. Anunay Yadav
    6. Chitrita Goswami
    7. Smriti Chawla
    8. Pierre Solomon
    9. Cynthia Fourgeux
    10. Gaurav Ahuja
    11. Brett Hollier
    12. Himanshu Kumar
    13. Antoine Roquilly
    14. Jeremie Poschmann
    15. Melanie Lehman
    16. Colleen C Nelson
    17. Debarka Sengupta
    This article has been curated by 1 group:
    • Curated by eLife

      eLife Assessment

      This manuscript presents an important contribution to the field of single-cell transcriptomic analysis in cancer by introducing a novel computational framework-SCellBOW-which applies embedding techniques from natural language processing to model phenotypic heterogeneity in tumors. The revised version includes new validation experiments and significant clarifications that provide convincing evidence for the method's utility. The authors have benchmarked SCellBOW across diverse datasets, including glioblastoma, breast, and metastatic prostate cancer, and have demonstrated its superior performance compared to existing state-of-the-art methods.

    Reviewed by eLife

    This article has 7 evaluationsAppears in 1 listLatest version Latest activity
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