Gene · 57477
Papers2,355
Newest first. Swiss-Prot's references are curated; PubTator's text mining finds papers that name the gene, not always ones about it.
281 to 300 of 2,355
Download this page as JSON| Title | Journal | Year | PMID | Found by | Source |
|---|---|---|---|---|---|
| Development and validation of a machine learning-based prediction model for malnutrition risk in peritoneal dialysis patients: a multi‑center retrospective study. | Int Urol Nephrol | 2026 | 42247202 | PubTator, text mining | PubMed |
| Predicting affinity and potency of new psychoactive substances at cannabinoid 1 receptor with explainable artificial intelligence. | Front Pharmacol | 2026 | 42244876 | PubTator, text mining | PubMed |
| Protein Predictors of Worsening Cerebral Edema in Traumatic Brain Injury in Critically Ill Patients. | bioRxiv | 2026 | 42244667 | PubTator, text mining | PubMed |
| Machine learning-based predictive factor analysis of depression among Chinese adolescents. | Front Psychiatry | 2026 | 42238088 | PubTator, text mining | PubMed |
| Dual swin transformer for assisting in the diagnosis and surgical prediction of necrotizing enterocolitis. | Pediatr Res | 2026 | 42236921 | PubTator, text mining | PubMed |
| Development and validation of a machine learning model predicting post-tonsillectomy hemorrhage. | Eur Arch Otorhinolaryngol | 2026 | 42228100 | PubTator, text mining | PubMed |
| Predicting adolescent suicidal tendency in Chinese secondary school students: a machine learning approach with XGBoost and SHAP interpretation. | BMC Public Health | 2026 | 42226135 | PubTator, text mining | PubMed |
| AI for predicting exacerbations in KIDs with asthma (AIRE-KIDS). | NPJ Digit Med | 2026 | 42225895 | PubTator, text mining | PubMed |
| A machine learning approach to quantifying fall conversion risk in fall-naïve Parkinson's patients. | Parkinsonism Relat Disord | 2026 | 42224911 | PubTator, text mining | PubMed |
| Machine learning-based screening model for Tic disorders comorbid with attention-deficit/hyperactivity disorder in children and SHAP value interpretation: a retrospective observational study. | Sci Rep | 2026 | 42218194 | PubTator, text mining | PubMed |
| Predicting short birth intervals in Bangladesh using stacked machine learning and SHAP explainability: evidence from BDHS 2022. | Reprod Health | 2026 | 42216193 | PubTator, text mining | PubMed |
| Integrating multi-omics and machine learning to explore the role of amino acid metabolism in intervertebral disk degeneration. | Front Neurol | 2026 | 42211301 | PubTator, text mining | PubMed |
| A multimodal machine learning model for predicting postoperative worsening of FOGQ in Parkinson's disease following STN-DBS. | Front Neurol | 2026 | 42211297 | PubTator, text mining | PubMed |
| Interpretable machine learning to predict NOAF in ICU patients with CKD: validation in US and Chinese cohorts. | Front Med (Lausanne) | 2026 | 42210929 | PubTator, text mining | PubMed |
| Harnessing machine learning to decode dietary Impacts on cardiometabolic multimorbidity. | Int J Med Inform | 2026 | 42208085 | PubTator, text mining | PubMed |
| Interpretable machine learning model for predicting hemorrhage following ultrasound-guided percutaneous renal biopsy: a multicenter study. | Abdom Radiol (NY) | 2026 | 42207295 | PubTator, text mining | PubMed |
| A Bedside Coagulation-Platelet Tipping Point for Mortality in Nontraumatic Subarachnoid Hemorrhage. | J Multidiscip Healthc | 2026 | 42206228 | PubTator, text mining | PubMed |
A CT-based multi-scale fusion model with SHAP interpretation for preoperative differentiation between lung adenocarcinoma in situ/minimally invasive adenocarcinoma and invasive adenocarcinoma: a multicenter study. | Front Oncol | 2026 | 42205745 | PubTator, text mining | PubMed |
| A Machine Learning Approach to Prognostication in Oral Cancer: Analysis of the Surveillance, Epidemiology, and End Results Database. | Cancer Inform | 2026 | 42205306 | PubTator, text mining | PubMed |
| A machine learning-based interpretable model for predicting pancreatic cancer in chronic pancreatitis patients with focal pancreatic lesions. | BMC Cancer | 2026 | 42204501 | PubTator, text mining | PubMed |
gene-search-2026-11-11-0.2.0
Sources 12
- ClinicalTrials.gov's posted results, through CTTI's AACTFreely available. Acknowledgement requested
- ChEMBL, through Open TargetsCC BY-SA 3.0
- ClinicalTrials.govNo license stated
- EMBL-EBI's patent proteinsNo added restrictions. Attribution expected
- GenBank's patent filesNo restrictions from NCBI. Submitters may hold rights
- HGNCCC0
- NCBI GenePublic domain (US government)
- NIH's project files and grant-paper linksPublic domain
- Open TargetsCC0 1.0
- PubMedNLM's terms
- PubTator 3Public domain
- UniProtCC BY 4.0
Each source's terms
- ClinicalTrials.gov's posted results, through CTTI's AACTClinicalTrials.gov data via Aggregate Analysis of ClinicalTrials.gov (AACT), CTTI. CTTI makes its materials freely available and requests acknowledgement. https://aact.ctti-clinicaltrials.org/documentation/299
- ChEMBL, through Open TargetsCC BY-SA 3.0, for the parts from ChEMBL. Read on 8 Nov 2026 at https://platform-docs.opentargets.org/licence
- ClinicalTrials.govnone stated
- EMBL-EBI's patent proteinsEMBL-EBI's patent protein files from the EPO, JPO, KIPO and USPTO. EMBL-EBI: "EMBL-EBI itself places no additional restrictions on the use or redistribution of the data available via its Data Resources and Tools other than those provided by the original data owners" and "EMBL-EBI expects attribution (e.g. in publications, services or products) for the use of any of its Data Resources and Tools." Read on 11 Nov 2026 at https://www.ebi.ac.uk/about/terms-of-use
- GenBank's patent filesGenBank's patent files. NCBI: "NCBI places no restrictions on the use or distribution of the GenBank data. However, some submitters may claim patent, copyright, or other intellectual property rights in all or a portion of the data they have submitted." Read on 11 Nov 2026 at https://www.ncbi.nlm.nih.gov/genbank/about/
- HGNCCC0: https://www.genenames.org/about/license/
- NCBI GeneNone named for the file. NCBI says information created by or for the US government on its site is in the public domain, and asks that NLM be acknowledged: https://www.ncbi.nlm.nih.gov/home/about/policies/
- NIH's project files and grant-paper linksPublic domain (NIH RePORTER)
- Open TargetsCC0 1.0. Open Targets asks that users cite its latest paper: Buniello et al. 2025, Open Targets Platform: facilitating therapeutic hypotheses building in drug discovery, Nucleic Acids Research 53(D1):D1467, PMID 39657122. Read on 8 Nov 2026 at https://platform-docs.opentargets.org/licence
- PubMedNLM's terms
- PubTator 3Public domain
- UniProtCC BY 4.0. UniProt's licence file: "All databases and documents in the UniProt FTP directory may be copied and redistributed freely, without advance permission, provided that this copyright statement is reproduced with each copy." UniProt asks that users cite its latest paper: The UniProt Consortium, UniProt: the Universal Protein Knowledgebase in 2025, Nucleic Acids Research 53:D609-D617, https://doi.org/10.1093/nar/gkae1010. Read on 9 Nov 2026 at https://www.uniprot.org/help/license
ClinicalTrials.gov's data carry an international copyright outside the United States: https://clinicaltrials.gov/about-site/terms-conditions.
For software
Read this list from software.
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GET https://conductscience.org/api/genes/v1/57477/papers?page=15