IS IT POSSIBLE TO PREDICT TUMOR PROGRESSION THROUGH GENOMIC CHARACTERIZATION OF MONOCLONAL GAMMOPATHY AND SMOLDERING MULTIPLE MYELOMA? by Ugo Testa, Giuseppe Leone, Elvira Pelosi, Germana Castelli, Valerio De Stefano

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A systems biology approach to prediction of oncogenes and molecular perturbation targets in B‐cell lymphomas by Kartik M Mani, Celine Lefebvre, Kai Wang, Wei Keat Lim, Katia Basso, Riccardo Dalla‐Favera, Andrea Califano

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Characteristics predicting reduced penetrance variants in the high-risk cancer predisposition gene TP53 by Cristina Fortuno, Marcy E. Richardson, Tina Pesaran, Kelly McGoldrick, Paul A. James, Amanda B. Spurdle

“…These variants also have a higher population frequency than pathogenic variants, and heterozygotes tend to manifest disease later in life, suggesting a need for refined clinical criteria to better capture attenuated Li-Fraumeni syndrome phenotypes. Finally, by applying a random forest prediction model to all TP53 uncertain or conflicting variants in ClinVar, we identified 106 additional variants with potential reduced penetrance.…”
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Decreased expression of TCF12 contributes to progression and predicts biochemical recurrence in patients with prostate cancer by Qing-biao Chen, Ying-ke Liang, Yan-qiong Zhang, Min-yao Jiang, Zhao-dong Han, Yu-xiang Liang, Yue-ping Wan, Jie Yin, Hui-Chan He, Wei-de Zhong

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Investigation of possible predictive factors, clinical characteristics, and treatment in vascular Behçet's disease: real-life data from a single center by Abdulvahap Kahveci, Zeycan Kübra Cevval

“… Objective: The aim of this study was to investigate the phenotypes, predictive factors, and treatment approach of Behçet's patients with vascular involvement.Material and Method: This retrospective study analyzed 123 patients with Behçet's disease, 28 of whom had vascular involvement, and were followed up in our center. …”
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Optimisation of variance component estimation and genomic prediction in a commercial crossbred population of Duroc x (Landrace x Yorkshire) three-way pigs by S. Liu, Z. Zhang

“…The combination of accurate VC estimation from random CB and the advantage of extreme phenotypic CB in prediction accuracy allows the mixed reference populations to achieve a superior predictive performance in GS. …”
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CADASIL: A NOTCH3-associated cerebral small vessel disease by Lamei Yuan, Xiangyu Chen, Joseph Jankovic, Hao Deng

“…However, since that time other genetic CSVDs have been described, including the HtrA serine peptidase 1 gene-associated CSVD and the cathepsin A gene-associated CSVD, that clinically mimic the original phenotype. Though NOTCH3-associated CSVD is now a well-recognized hereditary disorder and the number of studies investigating this disease is increasing, the role of NOTCH3 in the pathogenesis of CADASIL remains elusive. …”
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Does the IL-6/KL-6 ratio distinguish different phenotypes in COVID-19 Acute Respiratory Distress Syndrome? An observational study stemmed from prospectively derived clinical, biolo... by Nicolas Partouche, Myriam Maumy, Thien-Nga Chamaraux-Tran, Frederic Bertrand, Francis Schneider, Nicolas Meyer, Morgane Solis, Samira Fafi-Kremer, Eric Noll, Julien Pottecher

“…We hypothesized that the ratio of two pivotal COVID-19 biomarkers (interleukin 6 [IL-6] and Krebs von den Lungen 6 [KL-6], related to inflammation and pneumocyte repair, respectively) would provide a biologic insight into the disease timeline allowing 1) to differentiate H, I and L phenotypes, 2) to predict outcome and 3) to reflect some of CT findings.…”
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A compact encoding of the genome suitable for machine learning prediction of traits and genetic risk scores by Yasaman Fatapour, James P. Brody

“…Abstract Genotype to phenotype prediction is a central problem in biology and medicine. …”
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Powdery mildew resistance prediction in Barley (Hordeum Vulgare L) with emphasis on machine learning approaches by Farveh Vahidpour, Hossein Sabouri, Fakhtak Taliei, Sayed Javad Sajadi, Saeed Yarahmadi, Hossein Hosseini Moghaddam

“…Abstract By employing machine-learning models, this study utilizes agronomical and molecular features to predict powdery mildew disease resistance in Barley (Hordeum Vulgare L). …”
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Combining genome‐wide association and genomic prediction to unravel the genetic architecture of carotenoid accumulation in carrot by William R. Rolling, Shelby Ellison, Kevin Coe, Massimo Iorizzo, Julie Dawson, Douglas Senalik, Philipp W. Simon

“…We explored the accuracy of genomic prediction (GP) models to predict carotenoid concentration. …”
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Leveraging historical trials to predict Fusarium head blight resistance in spring wheat breeding programs by Charlotte Brault, Emily J. Conley, Andrew J. Green, Karl D. Glover, Jason P. Cook, Harsimardeep S. Gill, Andrew C. Read, Jason D. Fiedler, James A. Anderson

“…Furthermore, genotypic values were predicted in breeding programs using the URSN population as a training set with various prediction scenarios. …”
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In-Season Predictions Using Chlorophyll <i>a</i> Fluorescence for Selecting Agronomic Traits in Maize by Andrija Brkić, Sonja Vila, Domagoj Šimić, Antun Jambrović, Zvonimir Zdunić, Miroslav Salaić, Josip Brkić, Mirna Volenik, Vlatko Galić

“…Traditional maize (<i>Zea mays</i> L.) breeding approaches use directly measured phenotypic performance to make decisions for the next generation of crosses. …”
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Programmed cell death-driven remodeling of the melanoma microenvironment enables prognostic stratification and therapeutic prediction by Bo Hu, Shengnan Chai, Xuan Li, Qiang Zhang, Mei Jin, Long Zhang

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Identification of potential prognostic small nucleolar RNA biomarkers for predicting overall survival in patients with sarcoma by Jianwei Liu, Xiwen Liao, Xianze Zhu, Peizhen Lv, Rong Li

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PREDICTION OF LIVE WEIGHT THROUGH MORPHOMETRIC VARIABLES IN GOATS FROM BAJA CALIFORNIA SUR, MEXICO by Raul Avalos Castro, Jose Denis Osuna Amador, Noe Medina Cordova, Carlos Cabada Tavares, Jose C. Segura Correa

“…Regression models based on different morphometric measurements have been used as a practical, minimal cost and highly reliable method to predict live weight (LW) in goats; however, for the northwest region of Mexico there is no information available on the genetic and phenotypic variability of local goat populations, therefore, it is necessary to generate experiences on the efficiency of morphometric measurements to estimate LW in this area. …”
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Identification of a Gene Expression Signature to Predict the Risk of Abdominal Aortic Aneurysm in Psoriasis Patients by Lyu X, Tang Q, Zou Y, Liu X

“…The gene signature generated by these genes demonstrated high accuracy in predicting psoriasis and AAA. Using five algorithms for immune infiltration analysis, an abundance of inflammatory cells was observed in high-risk subgroups. …”
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varCADD: large sets of standing genetic variation enable genome-wide pathogenicity prediction by Lusiné Nazaretyan, Philipp Rentzsch, Martin Kircher

“…Abstract Background Machine learning and artificial intelligence are increasingly being applied to identify phenotypically causal genetic variation. These data-driven methods require comprehensive training sets to deliver reliable results. …”
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Machine learning-based prediction of antibiotic resistance in Mycobacterium tuberculosis clinical isolates from Uganda by Sandra Ruth Babirye, Mike Nsubuga, Gerald Mboowa, Charles Batte, Ronald Galiwango, David Patrick Kateete

“…HIV status was also identified among the top significant features in predicting drug resistance. Conclusion Leveraging machine learning applications in predicting antimicrobial resistance represents a promising avenue in addressing the global health challenge posed by antimicrobial resistance. …”
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MtCro: multi-task deep learning framework improves multi-trait genomic prediction of crops by Dian Chao, Hao Wang, Fengqiang Wan, Shen Yan, Wei Fang, Yang Yang

“…Furthermore, comparative analysis shows a consistent 2-3% improvement in multi-phenotype predictions, emphasizing the impact of inter-phenotype correlations on accuracy. …”
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