Dmitry A. Konovalov

Benchmarking of QSAR models for blood-brain barrier permeation.

Using the largest available database of 328 blood-brain distribution (logBB) values, a quantitative benchmark was proposed to allow for a consistent comparison of the predictive accuracy of current and future logBB/quantitative structure-activity relationship (-QSAR) models. The usefulness of the benchmark was illustrated by comparing the global and k-nearest neighbors (kNN) multiple-linear regression (MLR) models based on the linear free-energy relationship (LFER) descriptors, and one non-LFER-based MLR model. The leave-one-out (LOO) and leave-group-out Monte Carlo (MC) cross-validation results (q(2) = 0.766, qms = 0.290, and qms(mc) = 0.311) indicated that the LFER-based kNN-MLR model was currently one of the most accurate predictive logBB-QSAR models. The LOO, MC, and kNN-MLR methods have been implemented in the QSAR-BENCH program, which is freely available from www.dmitrykonovalov.org for academic use.

A Maximum-Likelihood relatedness estimator allowing for negative relatedness values

Previously reported maximum‐likelihood pairwise relatedness (r) estimator of Thompson and Milligan (M) was extended to allow for negative r estimates under the regression interpretation of r. This was achieved by establishing the equivalency of the likelihoods used in the kinship program and the likelihoods of Thompson. The new maximum‐likelihood (ML) estimator was evaluated by Monte Carlo simulations. It was found that the new ML estimator became unbiased significantly faster compared to the original M estimator when the amount of genotype information was increased. The effects of allele frequency estimation errors on the new and existing relatedness estimators were also considered.

TECHNICAL ADVANCES: A maximum-likelihood relatedness estimator allowing for negative relatedness values.

Previously reported maximum‐likelihood pairwise relatedness (r) estimator of Thompson and Milligan (M) was extended to allow for negative r estimates under the regression interpretation of r. This was achieved by establishing the equivalency of the likelihoods used in the kinship program and the likelihoods of Thompson. The new maximum‐likelihood (ML) estimator was evaluated by Monte Carlo simulations. It was found that the new ML estimator became unbiased significantly faster compared to the original M estimator when the amount of genotype information was increased. The effects of allele frequency estimation errors on the new and existing relatedness estimators were also considered.

Partition-distance via the assignment problem

MOTIVATION Accuracy testing of various pedigree reconstruction methods requires an efficient algorithm for the calculation of distance between a known partition and its reconstruction. The currently used algorithm of Almudevar and Field takes a prohibitively long time for certain partitions and population sizes. RESULTS We present an algorithm that very efficiently reduces the partition-distance calculation to the classic assignment problem of weighted bipartite graphs that has known polynomial-time solutions. The performance of the algorithm is tested against the Almudevar and Field partition-distance algorithm to verify the significant improvement in speed. AVAILABILITY Computer code written in java is available upon request from the first author.

Statistical Confidence for Variable Selection in QSAR Models via Monte Carlo Cross-Validation

A new variable selection wrapper method named the Monte Carlo variable selection (MCVS) method was developed utilizing the framework of the Monte Carlo cross-validation (MCCV) approach. The MCVS method reports the variable selection results in the most conventional and common measure of statistical hypothesis testing, the P-values, thus allowing for a clear and simple statistical interpretation of the results. The MCVS method is equally applicable to the multiple-linear-regression (MLR)-based or non-MLR-based quantitative structure-activity relationship (QSAR) models. The method was applied to blood-brain barrier (BBB) permeation and human intestinal absorption (HIA) QSAR problems using MLR to demonstrate the workings of the new approach. Starting from more than 1600 molecular descriptors, only two (TPSA(NO) and ALOGP) yielded acceptably low P-values for the BBB and HIA problems, respectively. The new method has been implemented in the QSAR-BENCH v2 program, which is freely available (including its Java source code) from www.dmitrykonovalov.org for academic use.

Modified SIMPSON O(n3) algorithm for the full sibship reconstruction problem

MOTIVATION The problem of reconstructing full sibling groups from DNA marker data remains a significant challenge for computational biology. A recently published heuristic algorithm based on Mendelian exclusion rules and the Simpson index was successfully applied to the full sibship reconstruction (FSR) problem. However, the so-called SIMPSON algorithm has an unknown complexity measure, questioning its applicability range. RESULTS We present a modified version of the SIMPSON (MS) algorithm that behaves as O(n(3)) and achieves the same or better accuracy when compared with the original algorithm. Performance of the MS algorithm was tested on a variety of simulated diploid population samples to verify its complexity measure and the significant improvement in efficiency (e.g. 100 times faster than SIMPSON in some cases). It has been shown that, in theory, the SIMPSON algorithm runs in non-polynomial time, significantly limiting its usefulness. It has been also verified via simulation experiments that SIMPSON could run in O(n(a)), where a > 3. AVAILABILITY Computer code written in Java is available upon request from the first author. CONTACT Dmitry.Konovalov@jcu.edu.au.

The role of electron-impact vibrational excitation in electron transport through gaseous tetrahydrofuran

In this paper, we report newly derived integral cross sections (ICSs) for electron impact vibrational excitation of tetrahydrofuran (THF) at intermediate impact energies. These cross sections extend the currently available data from 20 to 50 eV. Further, they indicate that the previously recommended THF ICS set [Garland et al., Phys. Rev. A 88, 062712 (2013)] underestimated the strength of the electron-impact vibrational excitation processes. Thus, that recommended vibrational cross section set is revised to address those deficiencies. Electron swarm transport properties were calculated with the amended vibrational cross section set, to quantify the role of electron-driven vibrational excitation in describing the macroscopic swarm phenomena. Here, significant differences of up to 17% in the transport coefficients were observed between the calculations performed using the original and revised cross section sets for vibrational excitation.

Differential cross sections for electron-impact vibrational-excitation of tetrahydrofuran at intermediate impact energies

We report differential cross sections (DCSs) for electron-impact vibrational-excitation of tetrahydrofuran, at intermediate incident electron energies (15-50 eV) and over the 10°-90° scattered electron angular range. These measurements extend the available DCS data for vibrational excitation for this species, which have previously been obtained at lower incident electron energies (≤20 eV). Where possible, our data are compared to the earlier measurements in the overlapping energy ranges. Here, quite good agreement was generally observed where the measurements overlapped.

Accuracy of four heuristics for the full sibship reconstruction problem in the presence of genotype errors

The full sibship reconstruction (FSR) problem is the problem of inferring all groups of full siblings from a given population sample using genetic marker data without parental information. The FSR problem remains a significant challenge for computational biology, since an exact solution for the problem has not been found. The new algorithm, named SIMPSON-assisted Descending Ratio (SDR), is devised combining a new Simpson index based O(n2) algorithm (MS2) and the existing Descending Ratio (DR) algorithm. The SDR algorithm outperforms the SIMPSON, MS2, and DR algorithms in accuracy and robustness when tested on a variety of sample family structures. The accuracy error is measured as the percentage of incorrectly assigned individuals. The robustness of the FSR algorithms is assessed by simulating a 2% mutation rate per locus (a 1% rate per allele).

Electron momentum spectroscopy of the isoelectronic species hydrogen fluoride and neon

The authors report new electron momentum spectroscopy (EMS) measurements on hydrogen fluoride (HF) and neon (Ne) at 1500 eV. The present HF data for the 1 pi , 3 sigma and 2 sigma orbitals are compared in detail with the results of an earlier EMS study at 400 and 1200 eV and with the results of a recent calculation of the valence orbital momentum distributions given by (i) SCF calculations at the Hartree-Fock limit and (ii) CI calculations of the complete molecule-ion overlap amplitude. The current Ne 2p and 2s momentum distributions are compared with the results of both the plane wave and a new, fully distorted wave Born approximation (DWBA) calculation. The results of the DWBA calculation in Ne have direct relevance to HF, in particular to the inner valence (2 sigma ) cross section.