Results 221 to 230 of about 2,151,311 (285)

Optimizing unsupervised feature engineering and classification pipelines for differentiated thyroid cancer recurrence prediction. [PDF]

BMC Med Inform Decis Mak
Onah E, Eze UJ, Abdulraheem AS, Ezigbo UG, Amorha KC, Ntie-Kang F.   +5 more
europepmc   +1 more source

Screening and epitope characterization of Nidogen‐2‐specific nanobodies

FEBS Open Bio, EarlyView.
Camel immunization and phage display were employed to generate high‐affinity VHH nanobodies against Nidogen‐2. After library construction, biopanning, ELISA screening, sequencing, and recombinant expression, selected nanobodies were purified and characterized, leading to the preliminary exploration of a nanobody‐based sandwich ELISA for specific ...
Jianchuan Wen, Qianqian Cui, Zhongyun Lan, Yingjun Wang, Shuaiying Zhao, Wenxuan Feng, Yunfeng Liu, Qiting Huang, Dongna Zhang, Jianfeng Xu   +9 more
wiley   +1 more source

UM-CPP: A Universal Model for Efficient Classification of Protein Particles in cryo-EM Micrographs with Feature Engineering. [PDF]

ACS Omega
Yao Z, Wang H, Luo W, Zhan Y, Wu X, Dai Y, Pei Y, Zhang G, Wang Z.   +8 more
europepmc   +1 more source

Matrix metalloproteinase‐9 regulates cell adhesion and membrane protrusive activity of ovarian cancer cells

FEBS Open Bio, EarlyView.
Matrix metalloproteinase‐9 (MMP9) drives ovarian cancer progression. Using MMP9‐null cells (M9‐KO) created from ovarian cancer cells, we found MMP9 loss did not block Epidermal Growth Factor (EGF)‐driven E‐cadherin dissolution or EMT but delayed and reduced EGF‐driven membrane protrusions. Transient MMP9 re‐expression drove membrane protrusion.
Claire Strauel, Sam Bennett, Natalie Ehlinger, Nelson Cook, Katelyn Marvin, Caleb L. Lines, Sam Reyes, Brooke Kirby, Shawn M. Ellerbroek   +8 more
wiley   +1 more source

Predicting drug-target interactions using machine learning with improved data balancing and feature engineering. [PDF]

Sci Rep
Talukder MA, Kazi M, Alazab A.
europepmc   +1 more source

Quantitative proteomic analysis reveals different characteristics of bladder cancer cells after exposure to bisphenol A

FEBS Open Bio, EarlyView.
Bisphenol A (BPA), a common chemical in plastics, exerts dual effects on bladder cancer cells: low doses promote growth and migration, while high doses suppress growth and migration. Multi‐omics and bioinformatics reveal BPA acts via MAPK and inflammatory pathways.
Shaomin Niu, Lanlan Li, Wenjuan Jia, Hanzhong Feng, Xiaoquan Yu, Youli Zhao, Fengzhi Yuan, Hui Ding, Junqiang Tian, Yong‐Xing He, Zhiping Wang   +10 more
wiley   +1 more source

CFG-DWC: a hybrid correlation-driven feature engineering framework for optimized machine learning performance in carbonation depth analysis of concrete subjected to natural environments. [PDF]

Sci Rep
Yilmaz Y, Çakmak T, Ustabaş İ.
europepmc   +1 more source

DrugProtAI: A machine learning-driven approach for predicting protein druggability through feature engineering and robust partition-based ensemble methods. [PDF]

Brief Bioinform
Halder A, Samantaray S, Barbade S, Gupta A, Srivastava S.   +4 more
europepmc   +1 more source

Predicting stock returns using machine learning combined with data envelopment analysis and automatic feature engineering: A case study on the Vietnamese stock market. [PDF]

PLoS One
Thanh Nhon H, Do-Thi N, Nguyen-Trang T.
europepmc   +1 more source

ECG-based heart arrhythmia classification using feature engineering and a hybrid stacked machine learning. [PDF]

BMC Cardiovasc Disord
Jahangir R, Islam MN, Islam MS, Islam MM.   +3 more
europepmc   +1 more source