Structural Analysis and Functional Prediction of Gut Microbiota in Wild and Cultured Striped Knifejaw (<i>Oplegnathus fasciatus</i>) by Kai Zhu, Susu Zhang, Kaida Xu, Haozhan Wang

Subjects: Get full text

Auto-branch multi-task learning for simultaneous prediction of multiple correlated traits associated with Alzheimer’s disease by Jiaqi Liang, Jiaqi Liang, Zhao Xue, Zhao Xue, Wenchao Zhou, Wenchao Zhou, Xiangjie Guo, Xiangjie Guo, Xiangjie Guo, Yalu Wen

Subjects: Get full text

Prediction of black soldier fly larval sex and morphological traits using computer vision and deep learning by Sarah Nawoya, Quentin Geissmann, Henrik Karstoft, Kim Bjerge, Roseline Akol, Andrew Katumba, Cosmas Mwikirize, Grum Gebreyesus

Get full text

Annotation-free deep learning algorithm trained on hematoxylin & eosin images predicts epithelial-to-mesenchymal transition phenotype and endocrine response in estrogen receptor-positive breast cancer by Kaimin Hu, Yinan Wu, Yajing Huang, Meiqi Zhou, Yanyan Wang, Xingru Huang

“…Our classifier achieved a predicting accuracy of 81.25%, and 88.7% slides labeled as endocrine resistant were predicted as the mesenchymal-phenotype, while 75.6% slides labeled as sensitive were predicted as the epithelial-phenotype. …”
Get full text

In silico analysis and high-risk pathogenic phenotype predictions of non-synonymous single nucleotide polymorphisms in human Crystallin beta A4 gene associated with congenital cataract. by Zhenyu Wang, Chen Huang, Huibin Lv, Mingzhou Zhang, Xuemin Li, Xuemin Li

Get full text

Hormonal predictors of the insulin sensitive phenotype in humans by Mohamed Badie Ahmed, Abdella M. Habib, Saif Badran, Abeer Alsherawi, Sherouk Essam Elnefaily, Mansour Binfayed, Atalla Hammouda, Graeme Glass, Ibrahem Abdalhakam, Abdul-Badi Abou-Samra, Suhail A. Doi

“…Notably, total body fat percentage did not predict ISP after accounting for hormonal factors. …”
Get full text

Partitioning the phenotypic and genetic variances of reaction norms by de Villemereuil, Pierre, Chevin, Luis-Miguel

“…We start by distinguishing the components of phenotypic variance arising from the average reaction norm across genotypes, genetic variation in reaction norms (with additive and non-additive components), and a residual that cannot be predicted from the genotype and the environment. …”
Get full text

GENOTYPE-PHENOTYPE CORRELATION IN CASES WITH LISSENCEPHALY SPECTRUM by Ayça Dilruba Aslanger, Zehra Oya Uyguner, Birsen Karaman, Seher Başaran, Hülya Kayserili Karabey

“…Objective: In this study, we aimed to evaluate six cases diagnosed with lissencephaly in terms of the genotype-phenotype correlation. Materials and Methods: Six cases with lissencephaly, which were followed up in our outpatient clinic, were included in the study. …”
Get full text

Frequency of imaging phenotypes of pulmonary interstitial fibrosis by Wallace T. Miller Jr, Scott Simpson, Shweta Sood, Michelle Hershman, Cheilonda R. Johnson, James E. Schmitt, Karen C. Patterson

“…Contribution: A flow diagram that predicts the relative frequency of the causes of 10 patterns of ILD.…”
Get full text

Role of Senescence-Associated Biomarkers and Immune Dynamics in Predicting Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer by Liu Y, Wu C, Lu X, Xue J

Subjects: “…senescence-associated secretory phenotype…”
Get full text

Population-based resequencing of APOA1 in 10,330 individuals: spectrum of genetic variation, phenotype, and comparison with extreme phenotype approach. by Christiane L Haase, Ruth Frikke-Schmidt, Børge G Nordestgaard, Anne Tybjærg-Hansen

“…Third, observed phenotypes were compared with those predicted using an extreme phenotype approach based on the apoA-I distribution. …”
Get full text

A graph convolutional network approach for hyperspectral image analysis of blueberries physiological traits under drought stress by Md. Hasibur Rahman, Savannah Busby, Sajid Hanif, Md Mesbahul Maruf, Faraz Ahmad, Sushan Ru, Alvaro Sanz-Saez, Jingyi Zheng, Tanzeel U. Rehman

Subjects: Get full text

Human Gut-Commensalic Lactobacillus ruminis ATCC 25644 Displays Sortase-Assembled Surface Piliation: Phenotypic Characterization of Its Fimbrial Operon through In Silico Predictive Analysis and Recombinant Expression in Lactococcus lactis. by Xia Yu, Annukka Jaatinen, Johanna Rintahaka, Ulla Hynönen, Outi Lyytinen, Ravi Kant, Silja Åvall-Jääskeläinen, Ingemar von Ossowski, Airi Palva

“…Heeding to in silico expectations, the predicted loci for the LrpCBA-called pili are organized tandemly in the L. ruminis genome as a canonical fimbrial operon, which then encodes for three pilin-proteins and a single C-type sortase enzyme. …”
Get full text

Application of a Multi-Spectral UAV Imagery in Germplasm Characterization: Prediction of Forage Biomass and Growth Patterns of Cicer Milkvetch (<i>Astragalus cicer</i> L.) Populati... by David MacTaggart, Steve Shirtliffe, Aaron Beattie, Herbert A. Lardner, Bill Biligetu

Get full text

Deep learning-based semantic segmentation for rice yield estimation by analyzing the dynamic change of panicle coverage by Hyeok-Jin Bak, Eun-Ji Kim, Ji-Hyeon Lee, Sungyul Chang, Dongwon Kwon, Woo-Jin Im, Woon-Ha Hwang, Jae-Ki Chang, Nam-Jin Chung, Wan-Gyu Sang

Subjects: Get full text

Breast cancer scoring based on a multiplexed profiling of soluble and cell-associated (immune) markers facilitates the prediction of pembrolizumab therapy by Verena Schweihofer, Christina Bruss, Stephan Seitz, Gunther Glehr, Madeleine Hetterich, Florian Weber, Maria Hatzipanagiotou, Miriam Fernández-Pacheco Álvarez, Olaf Ortmann, Gero Brockhoff, Richard J. Bauer, Anja Kathrin Wege

“…Thus, the identification of predictive biomarkers contributing to therapy response is urgently needed. …”
Get full text

The Eye of the Chiropterologist: Phenotypic Versus Genotypic Identification of Bats by F. D. Dami, T. E. Adeyanju, A. A. Chaskda, I. M. Okpanachi, A. T. Adeyanju, S. M. Ezekiel, T. Gwom, I. A. Iniunam, A. Hitch, D. D. Pam, P. Luka, S. C. Weaver, S. Paessler, R. W. Cross, N. Shehu

“…We then compared the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the phenotypic to the genotypic outcomes of our identification. …”
Get full text

Machine learning prediction of anxiety symptoms in social anxiety disorder: utilizing multimodal data from virtual reality sessions by Jin-Hyun Park, Yu-Bin Shin, Dooyoung Jung, Ji-Won Hur, Seung Pil Pack, Heon-Jeong Lee, Hwamin Lee, Chul-Hyun Cho, Chul-Hyun Cho

Get full text

Resource presentation dictates genetic and phenotypic adaptation in yeast by Neetika Ahlawat, Anjali Mahilkar, Supreet Saini

“…Conclusion This study highlights how subtle environmental differences dictate phenotypic and genetic adaptation of populations. Additionally, these results also suggest the predictive potential of ancestor’s fitness in understanding pleiotropic responses. …”
Get full text

Phenotyping sarcoidosis: a single institution retrospective analysis by Francesco Rocco Bertuccio, Francesco Rocco Bertuccio, Davide Piloni, Davide Piloni, Marianna Russo, Marianna Russo, Fady Tousa, Fady Tousa, Mariachiara Crescenzi, Mariachiara Crescenzi, Paola Putignano, Paola Putignano, Nicola Baio, Nicola Baio, Ida Maragò, Angelo Guido Corsico, Angelo Guido Corsico, Giulia Maria Stella, Giulia Maria Stella

“…For instance, finding a relationship between symptom burden, race, gender, HRQoL, and pulmonary function could have therapeutic ramifications, influence clinical practice, and aid in selecting patients for specific clinical studies.MethodsA comprehensive statistical evaluation was conducted using the JMP partitioning algorithm which explores all potential divisions to identify the most predictive variables.ResultsWith our analysis, we tried to categorize patients from a single Institution respiratory unit to delineate clinical phenotypes in sarcoidosis.ConclusionsLarger studies using appropriate methodology should surely be carried out to address this issue and help clarify the varying contributions of genetics, socioeconomic status, environmental exposures, and other sociodemographic factors to illness severity and phenotypic presentation. …”
Get full text