Bioinformatics

  1. Contrast Subgraphs Allow Comparing Homogeneous and Heterogeneous Networks Derived from Omics Data

    1. Tommaso Lanciano
    2. Aurora Savino
    3. Francesca Porcu
    4. Davide Cittaro
    5. Francesco Bonchi
    6. Paolo Provero

    Reviewed by GigaScience

    5 evaluationsAppears in 1 listLatest version Latest activity

  2. scShapes: a statistical framework for identifying distribution shapes in single-cell RNA-sequencing data

    1. Malindrie Dharmaratne
    2. Ameya S Kulkarni
    3. Atefeh Taherian Fard
    4. Jessica C Mar

    Reviewed by GigaScience

    1 evaluationAppears in 1 listLatest version Latest activity

  3. xAtlas: scalable small variant calling across heterogeneous next-generation sequencing experiments

    1. Jesse Farek
    2. Daniel Hughes
    3. William Salerno
    4. Yiming Zhu
    5. Aishwarya Pisupati
    6. Adam Mansfield
    7. Olga Krasheninina
    8. Adam C English
    9. Ginger Metcalf
    10. Eric Boerwinkle
    11. Donna M Muzny
    12. Richard Gibbs
    13. Ziad Khan
    14. Fritz J Sedlazeck

    Reviewed by GigaScience

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Accurate and Fast Clade Assignment via Deep Learning and Frequency Chaos Game Representation

    1. Jorge Avila Cartes
    2. Santosh Anand
    3. Simone Ciccolella
    4. Paola Bonizzoni
    5. Gianluca Della Vedova

    Reviewed by GigaScience

    1 evaluationAppears in 1 listLatest version Latest activity

  5. DeePVP: Identification and classification of phage virion proteins using deep learning

    1. Zhencheng Fang
    2. Tao Feng
    3. Hongwei Zhou
    4. Muxuan Chen

    Reviewed by GigaScience

    2 evaluationsAppears in 1 listLatest version Latest activity

  6. Stardust: improving spatial transcriptomics data analysis through space aware modularity optimization based clustering

    1. Simone Avesani
    2. Eva Viesi
    3. Luca Alessandrì
    4. Giovanni Motterle
    5. Vincenzo Bonnici
    6. Marco Beccuti
    7. Raffaele Calogero
    8. Rosalba Giugno

    Reviewed by GigaScience

    2 evaluationsAppears in 1 listLatest version Latest activity

  7. SurvBenchmark: comprehensive benchmarking study of survival analysis methods using both omics data and clinical data

    1. Yunwei Zhang
    2. Germaine Wong
    3. Graham Mann
    4. Samuel Muller
    5. Jean Y H Yang

    Reviewed by GigaScience

    2 evaluationsAppears in 1 listLatest version Latest activity

  8. Meta-Prism 2.0: Enabling algorithm for ultra-fast, accurate and memory-efficient search among millions of microbial community samples

    1. Kai Kang
    2. Hui Chong
    3. Kang Ning

    Reviewed by GigaScience

    1 evaluationAppears in 1 listLatest version Latest activity

  9. Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations

    1. M Elise Lauterbur
    2. Maria Izabel A Cavassim
    3. Ariella L Gladstein
    4. Graham Gower
    5. Nathaniel S Pope
    6. Georgia Tsambos
    7. Jeffrey Adrion
    8. Saurabh Belsare
    9. Arjun Biddanda
    10. Victoria Caudill
    11. Jean Cury
    12. Ignacio Echevarria
    13. Benjamin C Haller
    14. Ahmed R Hasan
    15. Xin Huang
    16. Leonardo Nicola Martin Iasi
    17. Ekaterina Noskova
    18. Jana Obsteter
    19. Vitor Antonio Correa Pavinato
    20. Alice Pearson
    21. David Peede
    22. Manolo F Perez
    23. Murillo F Rodrigues
    24. Chris CR Smith
    25. Jeffrey P Spence
    26. Anastasia Teterina
    27. Silas Tittes
    28. Per Unneberg
    29. Juan Manuel Vazquez
    30. Ryan K Waples
    31. Anthony Wilder Wohns
    32. Yan Wong
    33. Franz Baumdicker
    34. Reed A Cartwright
    35. Gregor Gorjanc
    36. Ryan N Gutenkunst
    37. Jerome Kelleher
    38. Andrew D Kern
    39. Aaron P Ragsdale
    40. Peter L Ralph
    41. Daniel R Schrider
    42. Ilan Gronau

    • Curated by eLife

      eLife assessment

      This important paper reports recent improvements and extensions to stdpopsim, a community-driven resource that is built on top of powerful software for performing simulations of population genomic data and provides a catalog of species with curated genomic parameters and demographic models. In addition to describing the new features and species in stdpopsim, the authors provide a set of practical guidelines for implementing realistic simulations. Overall, this convincing manuscript serves as an excellent overview of the utility, challenges, common pitfalls, and best practices of population genomic simulations. It will be of broad interest to population, evolutionary, and ecological geneticists studying humans, model organisms, or non-model organisms.

    Reviewed by eLife

    10 evaluationsAppears in 1 listLatest version Latest activity

  10. A transfer-learning approach to predict antigen immunogenicity and T-cell receptor specificity

    1. Barbara Bravi
    2. Andrea Di Gioacchino
    3. Jorge Fernandez-de-Cossio-Diaz
    4. Aleksandra M Walczak
    5. Thierry Mora
    6. Simona Cocco
    7. Rémi Monasson

    • Curated by eLife

      eLife assessment

      In this important work, the authors present a sequence-based approach using transfer learning and Restricted Boltzmann Machines to predict antigen immunogenicity and specificity. The evidence and methodology are compelling. This work should be of interest to immunologists, computational biologists, and biophysicists.

    Reviewed by eLife

    4 evaluationsAppears in 1 listLatest version Latest activity
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