Results 71 to 80 of about 9,752,550 (347)
Reconstructing enzyme evolution by protein engineering
FEBS Letters, EarlyView.Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler +2 more
wiley +1 more source
Greedy Algorithm for Deriving Decision Rules from Decision Tree Ensembles
EntropyThis study introduces a greedy algorithm for deriving decision rules from decision tree ensembles, targeting enhanced interpretability and generalization in distributed data environments.
Evans Teiko Tetteh, Beata Zielosko
doaj +1 more source
Extension of Decision Tree Algorithm for Stream Data Mining Using Real Data [PDF]
, 2009 Recently, because of increasing amount of data in the society, data stream mining targeting large scale data has attracted attention. The data mining is a technology of discovery new knowledge and patterns from the massive amounts of data, and what the ...
Konishi, Osamu +3 more
core
Fuzzy decision tree based analysis of databases
, 2008 The general fuzzy decision tree approach encapsulates the benefits of being an inductive learning technique to classify objects, utilising the richness of the data being considered, as well as the readability and interpretability that accompanies its ...
Beynon, Malcolm James, Malcolm Beynon
core +1 more source
Liver organoids: modelling complexity in homeostasis and disease
FEBS Letters, EarlyView.Studying liver in vitro has been challenging because simple 2D cell cultures fail to capture liver's cellular and architectural complexity. To bridge this gap, scientists increasingly use organoids, 3D liver models which better mimic liver composition and function. This review examines recent advances in liver organoid complexity and realism, discusses
Anna M. Dowbaj, Meritxell Huch
wiley +1 more source
, 2020 Decision tree is a supervised machine learning algorithm suitable for solving classification and regression problems. Decision trees are recursively built by applying split conditions at each node that divides the training records into subsets with ...
Suryakanthi Tangirala
semanticscholar +1 more source
A Detailed Review on Decision Tree and Random Forest
Bioscience Biotechnology Research Communications, 2020 The decision tree method works by repeatedly dividing the location of features into imaginary limb regions so that each imaginary location provides a basis for making a different approximation.
Bhushan Talekar
semanticscholar +1 more source
MITF maintains genome stability in nonmelanocyte lineages
Molecular Oncology, EarlyView.MITF is essential for melanocyte survival and acts as an oncogene in 10%–20% of melanomas. We show that MITF depletion causes genome instability in nonmelanocytic cells, leading to LATS2‐mediated P53 activation, cell cycle arrest, and apoptosis. This study highlights the role of MITF as a genome maintenance factor beyond the melanocyte lineage. Created
Drifa H. Gudmundsdottir +13 more
wiley +1 more source
Decision tree analysis for prostate cancer prediction [PDF]
Srpski Arhiv za Celokupno Lekarstvo, 2019 Introduction/Objective. The use of serum prostate-specific antigen (PSA) test has dramatically increased the number of men undergoing prostate biopsy. However, the best possible strategies for selecting appropriate patients for prostate biopsy have yet ...
Stojadinović Miroslav M. +2 more
doaj +1 more source