Results 121 to 130 of about 1,819,138 (329)

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, Markus R. Busch, Reinhard Sterner   +2 more
wiley   +1 more source

Respecting Markov equivalence in computing posterior probabilities of causal graphical features

, 2010
There have been many efforts to identify causal graphical features such as directed edges between random variables from observational data. Recently, Tian et al.
Kang, Eun Yong, Kang, E.Y., Shpitser, Ilya, Eskin, E., Eskin, Eleazar   +4 more
core   +1 more source

Foundations of causal discovery on groups of variables

Journal of Causal Inference
Discovering causal relationships from observational data is a challenging task that relies on assumptions connecting statistical quantities to graphical or algebraic causal models.
Wahl Jonas, Ninad Urmi, Runge Jakob
doaj   +1 more source

Investigating transcription factor dynamics in health and disease using FRAP

FEBS Letters, EarlyView.
FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj, Carolina Vazquez Garzon, Jose Joaquin Velasco, Janine N. Post   +3 more
wiley   +1 more source

Dagma-DCE: Interpretable, Non-Parametric Differentiable Causal Discovery

IEEE Open Journal of Signal Processing
We introduce Dagma-DCE, an interpretable and model-agnostic scheme for differentiable causal discovery. Current non- or over-parametric methods in differentiable causal discovery use opaque proxies of “independence” to justify the inclusion
Daniel Waxman, Kurt Butler, Petar M. Djuric   +2 more
doaj   +1 more source

Causal Discovery for Manufacturing Domains

CoRR, 2016
Yield and quality improvement is of paramount importance to any manufacturing company. One of the ways of improving yield is through discovery of the root causal factors affecting yield. We propose the use of data-driven interpretable causal models to identify key factors affecting yield.
Katerina Marazopoulou, Rumi Ghosh, Prasanth Lade, David D. Jensen   +3 more
openaire   +2 more sources

TRAIL‐PEG‐Apt‐PLGA nanosystem as an aptamer‐targeted drug delivery system potential for triple‐negative breast cancer therapy using in vivo mouse model

Molecular Oncology, Volume 20, Issue 7, Page 1742-1761, July 2026.
Aptamers are used both therapeutically and as targeting agents in cancer treatment. We developed an aptamer‐targeted PLGA–TRAIL nanosystem that exhibited superior therapeutic efficacy in NOD/SCID breast cancer models. This nanosystem represents a novel biotechnological drug candidate for suppressing resistance development in breast cancer.
Gulen Melike Demirbolat, Aslihan Kucuk, Omer Erdogan, Samed Ozer, Bensu Kozan, Tugba Cuceli, Erkan Gumus, Evrim Cevik, Ozge Cevik   +8 more
wiley   +1 more source

Causal Modelling Agents: Causal Graph Discovery through Synergising Metadata- and Data-driven Reasoning [PDF]

Scientific discovery hinges on the effective integration of metadata, which refers to a set of conceptual operations such as determining what information is relevant for inquiry, and data, which encompasses physical operations such as observation and ...
Drobnjak, I, He, T, Castro, DC, Abdulaal, A, Alexander, DC, Montaña-Brown, N, Hadjivasiliou, A, Ijishakin, A   +7 more
core  

Structural gating and effect-aligned lag-resolved temporal causal discovery framework with application to heat–pollution extremes

Green Technologies and Sustainability
This study proposes Structural Gating and Effect-aligned Discovery for Temporal Causal Discovery (SGED-TCD), a novel and general framework for lag-resolved causal discovery in complex multivariate time series. SGED-TCD combines explicit structural gating,
Rui Chen, Jinsong Wu
doaj   +1 more source

Tumour–host interactions in Drosophila: mechanisms in the tumour micro‐ and macroenvironment

Molecular Oncology, EarlyView.
This review examines how tumour–host crosstalk takes place at multiple levels of biological organisation, from local cell competition and immune crosstalk to organism‐wide metabolic and physiological collapse. Here, we integrate findings from Drosophila melanogaster studies that reveal conserved mechanisms through which tumours hijack host systems to ...
José Teles‐Reis, Tor Erik Rusten
wiley   +1 more source