32 research outputs found
A Process Mining Approach to Statistical Analysis: Application to a Real-World Advanced Melanoma Dataset
AbstractThanks to its ability to offer a time-oriented perspective on the clinical events that define the patient's path of care, Process Mining (PM) is assuming an emerging role in clinical data analytics. PM's ability to exploit time-series data and to build processes without any a priori knowledge suggests interesting synergies with the most common statistical analyses in healthcare, in particular survival analysis. In this work we demonstrate contributions of our process-oriented approach in analyzing a real-world retrospective dataset of patients treated for advanced melanoma at the Lausanne University Hospital. Addressing the clinical questions raised by our oncologists, we integrated PM in almost all the steps of a common statistical analysis. We show: (1) how PM can be leveraged to improve the quality of the data (data cleaning/pre-processing), (2) how PM can provide efficient data visualizations that support and/or suggest clinical hypotheses, also allowing to check the consistency between real and expected processes (descriptive statistics), and (3) how PM can assist in querying or re-expressing the data in terms of pre-defined reference workflows for testing survival differences among sub-cohorts (statistical inference). We exploit a rich set of PM tools for querying the event logs, inspecting the processes using statistical hypothesis testing, and performing conformance checking analyses to identify patterns in patient clinical paths and study the effects of different treatment sequences in our cohort
Substrate-modulated unwinding of transmembrane helices in the NSS transporter LeuT:Recommended in F1000Prime as being of special significance in its field by F1000 Faculty Member Robert Vandenberg
The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases
The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article
Serum protein predictors of long term survival from combined ipilimumab and nivolumab therapy in metastatic melanoma patients.
Statistical Mechanical Derivation of Jarzynski’s Identity for Thermostated Non-Hamiltonian Dynamics
Molecular Dynamics Simulation Study of a Mutant Construct of the Archaeal Glutamate Transporter GltPh with Transport Rates as Fast as its Human Counterpart
Alchemical Free Energy Differences in Flexible Molecules from Thermodynamic Integration or Free Energy Perturbation Combined with Driven Adiabatic Dynamics
Alchemical free energy simulations are commonly used
to calculate
relative binding or solvation free energies in molecular systems.
The convergence of alchemical free energy calculations is often hampered
by inefficient sampling of the conformational degrees of freedom,
which remain trapped in metastable substates. Here, we show that thermodynamic
integration (TI) or free energy perturbation (FEP) can be combined
with the recent driven adiabatic free energy dynamics (dAFED) method,
in order to enhance conformational sampling along a set of chosen
collective variables. The resulting TI-dAFED or FEP-dAFED methods
are validated on a two-dimensional analytical problem. The ability
of these methods to provide accurate free energy differences for realistic
molecular systems is demonstrated by calculating the enantiomerization
free energy of the alanine dipeptide in explicit solvent
Free Energy Reconstruction from Metadynamics or Adiabatic Free Energy Dynamics Simulations
In molecular dynamics simulations,
most enhanced sampling methods
are traditionally associated with one particular estimator to calculate
the free energy surface (FES), such as the histogram, the mean force,
or the bias potential. Here, we start from the realization that four
enhanced sampling methods, metadynamics and well-tempered metadynamics
(in their extended Lagrangian form), as well as driven adiabatic free
energy dynamics (dAFED) and unified free energy dynamics (UFED), can
be used in combination with any of the three above-mentioned FES estimators.
We compare the convergence properties of these estimators on the alanine
dipeptide and a sodium ion solvation shell. We find that the mean
force estimator is superior in all cases. We also show that it can
be marginally beneficial to combine information from the histogram
and the force, provided that both are of comparable accuracy