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Predicting Transcription Factor Binding Sites with Deep Learning.

Ghosh N, Santoni D, Saha I, Felici G. · International journal of molecular sciences · 2024 · Journal publication

Original publication · Original publication · Original publication

Recorded summary

Reference associated with Fractal TFBS Analysis / Fractal Chromatin 3D Organisation.

Recorded limitations

Bibliographic metadata matched; scientific claims await appraisal.

Evidence and provenance

Chapter Trust Factor uses a minimum of three distinct qualifying studies. Publication records retain their own evidence and assessment.

Study design and assessment
design
Journal publication
assessment
Not recorded
trust Factor
scope
Paper
status
unassessed
score
Not recorded
basis
Bibliographic identity checks do not establish study design, blinding or evidential strength.
jadad
status
unassessed
score
Not recorded
evidence
Not recorded
Topics and recorded topic scores
  1. key
    general:imaging-transcriptomics
    title
    Imaging, Transcriptomics and Gene Regulation
    collection
    general
    trust Score
    Not recorded
Citation snapshot and identifiers
id
hsi-6963bd6166bcd0
doi
10.3390/ijms25094990
pmid
38732207
citation Snapshot
Not recorded
citations By Collection
general
Not recorded
Complete approved library record
id
hsi-6963bd6166bcd0
aliases
None recorded
source References
  1. ref
    NPL-219
    record Id
    hsi-6963bd6166bcd0
    source Type
    Journal publication
    title
    Predicting Transcription Factor Binding Sites with Deep Learning.
    authors
    Ghosh N, Santoni D, Saha I, Felici G.
    year
    2024
    journal
    International journal of molecular sciences
    doi
    10.3390/ijms25094990
    pmid
    38732207
    pmcid
    PMC11084193
    patent Number
    Not recorded
    original Assignee
    Not recorded
    original Citation
    Ghosh N, Santoni D, Saha I, Felici G (2024). "Predicting Transcription Factor Binding Sites with Deep Learning." International Journal of Molecular Sciences 25(9):4990. DOI: 10.3390/ijms25094990 — DNABERT-Cap: transformer-based capsule network for TFBS prediction; AUC > 0.91 across five ENCODE cell lines; cross-cell line prediction demonstrates intrinsic TFBS pattern transfer; TFs absent from training recognised with high accuracy (e.g., Znf143 AUC = 0.968, SMC3 AUC > 0.95)
    original Section
    Fractal TFBS Analysis / Fractal Chromatin 3D Organisation
    metadata Status
    metadata-matched
    claim Review
    Not independently appraised
    source URL
    https://www.notion.so/3807b9c99c5680599be7d8337c817b15
    publication URL
    https://pubmed.ncbi.nlm.nih.gov/38732207/
    metadata URL
    https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=DOI%3A%2210.3390%2Fijms25094990%22&format=json&resultType=core&pageSize=4
    corrections
    None recorded
    topic Id
    imaging-transcriptomics
    role
    Focused chapter source
source Type
Journal publication
source Verification
Bibliographic metadata matched; scientific claims await appraisal.
source Collection
Hyperspectral Imaging · patent section 2.4
title
Predicting Transcription Factor Binding Sites with Deep Learning.
journal
International journal of molecular sciences
neurotransmitters
None recorded
year
2024
authors
Ghosh N, Santoni D, Saha I, Felici G.
design
Journal publication
kind
Journal publication
identity Conflict
Not recorded
doi
10.3390/ijms25094990
pmid
38732207
urls

https://pubmed.ncbi.nlm.nih.gov/38732207/ · https://doi.org/10.3390/ijms25094990 · https://pmc.ncbi.nlm.nih.gov/articles/PMC11084193/

collections

general

categories

Hyperspectral Imaging

targets
None recorded
priority
1
quotes
None recorded
summary
Reference associated with Fractal TFBS Analysis / Fractal Chromatin 3D Organisation.
limitation
Bibliographic metadata matched; scientific claims await appraisal.
citation Count
Not recorded
paper Trust Assessment
scope
Paper
status
unassessed
score
Not recorded
basis
Bibliographic identity checks do not establish study design, blinding or evidential strength.
citations By Collection
general
Not recorded
topics
  1. key
    general:imaging-transcriptomics
    title
    Imaging, Transcriptomics and Gene Regulation
    collection
    general
    trust Score
    Not recorded
journal Key
internationaljournalofmolecularsciences
journal Label
International journal of molecular sciences
chapter Entries
  1. id
    general-imaging-transcriptomics-hsi-6963bd6166bcd0
    record Id
    hsi-6963bd6166bcd0
    title
    Predicting Transcription Factor Binding Sites with Deep Learning.
    journal
    International journal of molecular sciences
    year
    2024
    authors
    Ghosh N, Santoni D, Saha I, Felici G.
    design
    Journal publication
    urls

    https://pubmed.ncbi.nlm.nih.gov/38732207/ · https://doi.org/10.3390/ijms25094990 · https://pmc.ncbi.nlm.nih.gov/articles/PMC11084193/

    quotes
    None recorded
    summary
    Reference associated with Fractal TFBS Analysis / Fractal Chromatin 3D Organisation.
    related Versions
    None recorded
    limitation
    Bibliographic metadata matched; scientific claims await appraisal.
    citation Count
    Not recorded
    source Pages
    None recorded
    doi
    10.3390/ijms25094990
    pmid
    38732207
    targets
    None recorded
    categories

    Hyperspectral Imaging

    source References
    1. ref
      NPL-219
      record Id
      hsi-6963bd6166bcd0
      source Type
      Journal publication
      title
      Predicting Transcription Factor Binding Sites with Deep Learning.
      authors
      Ghosh N, Santoni D, Saha I, Felici G.
      year
      2024
      journal
      International journal of molecular sciences
      doi
      10.3390/ijms25094990
      pmid
      38732207
      pmcid
      PMC11084193
      patent Number
      Not recorded
      original Assignee
      Not recorded
      original Citation
      Ghosh N, Santoni D, Saha I, Felici G (2024). "Predicting Transcription Factor Binding Sites with Deep Learning." International Journal of Molecular Sciences 25(9):4990. DOI: 10.3390/ijms25094990 — DNABERT-Cap: transformer-based capsule network for TFBS prediction; AUC > 0.91 across five ENCODE cell lines; cross-cell line prediction demonstrates intrinsic TFBS pattern transfer; TFs absent from training recognised with high accuracy (e.g., Znf143 AUC = 0.968, SMC3 AUC > 0.95)
      original Section
      Fractal TFBS Analysis / Fractal Chromatin 3D Organisation
      metadata Status
      metadata-matched
      claim Review
      Not independently appraised
      source URL
      https://www.notion.so/3807b9c99c5680599be7d8337c817b15
      publication URL
      https://pubmed.ncbi.nlm.nih.gov/38732207/
      metadata URL
      https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=DOI%3A%2210.3390%2Fijms25094990%22&format=json&resultType=core&pageSize=4
      corrections
      None recorded
      topic Id
      imaging-transcriptomics
      role
      Focused chapter source
    source Type
    Journal publication
    source Verification
    Bibliographic metadata matched; scientific claims await appraisal.
    collection
    general
    chapter Number
    11
    topic Id
    imaging-transcriptomics
    topic Title
    Imaging, Transcriptomics and Gene Regulation
    trust Score
    Not recorded
    paper Trust Assessment
    scope
    Paper
    status
    unassessed
    score
    Not recorded
    basis
    Bibliographic identity checks do not establish study design, blinding or evidential strength.
jadad
status
unassessed
score
Not recorded
condition Evidence
None recorded
conditions
None recorded
topic Trust Scores
None recorded
full Text
status
not-indexed
retrieval Available
false

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