Modeling sequencing errors by combining Hidden Markov models.

Among the largest resources for biological sequence data is the large amount of expressed sequence tags (ESTs) available in public and proprietary databases. ESTs provide information on transcripts but for technical reasons they often contain sequencing errors. Therefore, when analyzing EST sequences computationally, such errors must be taken into account. Earlier attempts to model error prone coding regions have shown good performance in detecting and predicting these while correcting sequencing errors using codon usage frequencies. In the research presented here, we improve the detection of translation start and stop sites by integrating a more complex mRNA model with codon usage bias based error correction into one hidden Markov model (HMM), thus generalizing this error correction approach to more complex HMMs. We show that our method maintains the performance in detecting coding sequences.

Evaluating the influence of spatial uncertainty in locality points for species distributional modeling

1. Species distribution modelling is used increasingly in both applied and theoretical research to predict how species are distributed and to understand attributes of species' environmental requirements. In species distribution modelling, various statistical methods are used that combine species occurrence data with environmental spatial data layers to predict the suitability of any site for that species. While the number of data sharing initiatives involving species' occurrences in the scientific community has increased dramatically over the past few years, various data quality and methodological concerns related to using these data for species distribution modelling have not been addressed adequately. 2. We evaluated how uncertainty in georeferences and associated locational error in occurrences influence species distribution modelling using two treatments: (1) a control treatment where models were calibrated with original, accurate data and (2) an error treatment where data were first degraded spatially to simulate locational error. To incorporate error into the coordinates, we moved each coordinate with a random number drawn from the normal distribution with a mean of zero and a standard deviation of 5 km. We evaluated the influence of error on the performance of 10 commonly used distributional modelling techniques applied to 40 species in four distinct geographical regions. 3. Locational error in occurrences reduced model performance in three of these regions; relatively accurate predictions of species distributions were possible for most species, even with degraded occurrences. Two species distribution modelling techniques, boosted regression trees and maximum entropy, were the best performing models in the face of locational errors. The results obtained with boosted regression trees were only slightly degraded by errors in location, and the results obtained with the maximum entropy approach were not affected by such errors. 4. Synthesis and applications. To use the vast array of occurrence data that exists currently for research and management relating to the geographical ranges of species, modellers need to know the influence of locational error on model quality and whether some modelling techniques are particularly robust to error. We show that certain modelling techniques are particularly robust to a moderate level of locational error and that useful predictions of species distributions can be made even when occurrence data include some error.

Multimodel inference and multimodel averaging in empirical modeling of occupational exposure levels.

Empirical modeling of exposure levels has been popular for identifying exposure determinants in occupational hygiene. Traditional data-driven methods used to choose a model on which to base inferences have typically not accounted for the uncertainty linked to the process of selecting the final model. Several new approaches propose making statistical inferences from a set of plausible models rather than from a single model regarded as 'best'. This paper introduces the multimodel averaging approach described in the monograph by Burnham and Anderson. In their approach, a set of plausible models are defined a priori by taking into account the sample size and previous knowledge of variables influent on exposure levels. The Akaike information criterion is then calculated to evaluate the relative support of the data for each model, expressed as Akaike weight, to be interpreted as the probability of the model being the best approximating model given the model set. The model weights can then be used to rank models, quantify the evidence favoring one over another, perform multimodel prediction, estimate the relative influence of the potential predictors and estimate multimodel-averaged effects of determinants. The whole approach is illustrated with the analysis of a data set of 1500 volatile organic compound exposure levels collected by the Institute for work and health (Lausanne, Switzerland) over 20 years, each concentration having been divided by the relevant Swiss occupational exposure limit and log-transformed before analysis. Multimodel inference represents a promising procedure for modeling exposure levels that incorporates the notion that several models can be supported by the data and permits to evaluate to a certain extent model selection uncertainty, which is seldom mentioned in current practice.

MAMOT: hidden Markov modeling tool.

Hidden Markov models (HMMs) are probabilistic models that are well adapted to many tasks in bioinformatics, for example, for predicting the occurrence of specific motifs in biological sequences. MAMOT is a command-line program for Unix-like operating systems, including MacOS X, that we developed to allow scientists to apply HMMs more easily in their research. One can define the architecture and initial parameters of the model in a text file and then use MAMOT for parameter optimization on example data, decoding (like predicting motif occurrence in sequences) and the production of stochastic sequences generated according to the probabilistic model. Two examples for which models are provided are coiled-coil domains in protein sequences and protein binding sites in DNA. A wealth of useful features include the use of pseudocounts, state tying and fixing of selected parameters in learning, and the inclusion of prior probabilities in decoding. AVAILABILITY: MAMOT is implemented in C++, and is distributed under the GNU General Public Licence (GPL). The software, documentation, and example model files can be found at http://bcf.isb-sib.ch/mamot

Homology modeling and metabolism prediction of human carboxylesterase-2 using docking analyses by GriDock: a parallelized tool based on AutoDock 4.0.

Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted to developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas less has been done to predict the activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES2. The study involved first a homology modeling of the hCES2 protein based on the model of hCES1 since the two proteins share a high degree of homology (congruent with 73%). A set of 40 known substrates of hCES2 was taken from the literature; the ligands were docked in both their neutral and ionized forms using GriDock, a parallel tool based on the AutoDock4.0 engine which can perform efficient and easy virtual screening analyses of large molecular databases exploiting multi-core architectures. Useful statistical models (e.g., r (2) = 0.91 for substrates in their unprotonated state) were calculated by correlating experimental pK(m) values with distance between the carbon atom of the substrate's ester group and the hydroxy function of Ser228. Additional parameters in the equations accounted for hydrophobic and electrostatic interactions between substrates and contributing residues. The negatively charged residues in the hCES2 cavity explained the preference of the enzyme for neutral substrates and, more generally, suggested that ligands which interact too strongly by ionic bonds (e.g., ACE inhibitors) cannot be good CES2 substrates because they are trapped in the cavity in unproductive modes and behave as inhibitors. The effects of protonation on substrate recognition and the contrasting behavior of substrates and products were finally investigated by MD simulations of some CES2 complexes.

Use of DNA profiles for investigation using a simulated national DNA database: Part II. Statistical and ethical considerations on familial searching.

Familial searching consists of searching for a full profile left at a crime scene in a National DNA Database (NDNAD). In this paper we are interested in the circumstance where no full match is returned, but a partial match is found between a database member's profile and the crime stain. Because close relatives share more of their DNA than unrelated persons, this partial match may indicate that the crime stain was left by a close relative of the person with whom the partial match was found. This approach has successfully solved important crimes in the UK and the USA. In a previous paper, a model, which takes into account substructure and siblings, was used to simulate a NDNAD. In this paper, we have used this model to test the usefulness of familial searching and offer guidelines for pre-assessment of the cases based on the likelihood ratio. Siblings of "persons" present in the simulated Swiss NDNAD were created. These profiles (N=10,000) were used as traces and were then compared to the whole database (N=100,000). The statistical results obtained show that the technique has great potential confirming the findings of previous studies. However, effectiveness of the technique is only one part of the story. Familial searching has juridical and ethical aspects that should not be ignored. In Switzerland for example, there are no specific guidelines to the legality or otherwise of familial searching. This article both presents statistical results, and addresses criminological and civil liberties aspects to take into account risks and benefits of familial searching.

Assessment of statistical iterative reconstructions to optimize CT examination protocols for children and young adults

La tomodensitométrie (CT) est une technique d'imagerie dont l'intérêt n'a cessé de croître depuis son apparition dans le début des années 70. Dans le domaine médical, son utilisation est incontournable à tel point que ce système d'imagerie pourrait être amené à devenir victime de son succès si son impact au niveau de l'exposition de la population ne fait pas l'objet d'une attention particulière. Bien évidemment, l'augmentation du nombre d'examens CT a permis d'améliorer la prise en charge des patients ou a rendu certaines procédures moins invasives. Toutefois, pour assurer que le compromis risque - bénéfice soit toujours en faveur du patient, il est nécessaire d'éviter de délivrer des doses non utiles au diagnostic.¦Si cette action est importante chez l'adulte elle doit être une priorité lorsque les examens se font chez l'enfant, en particulier lorsque l'on suit des pathologies qui nécessitent plusieurs examens CT au cours de la vie du patient. En effet, les enfants et jeunes adultes sont plus radiosensibles. De plus, leur espérance de vie étant supérieure à celle de l'adulte, ils présentent un risque accru de développer un cancer radio-induit dont la phase de latence peut être supérieure à vingt ans. Partant du principe que chaque examen radiologique est justifié, il devient dès lors nécessaire d'optimiser les protocoles d'acquisitions pour s'assurer que le patient ne soit pas irradié inutilement. L'avancée technologique au niveau du CT est très rapide et depuis 2009, de nouvelles techniques de reconstructions d'images, dites itératives, ont été introduites afin de réduire la dose et améliorer la qualité d'image.¦Le présent travail a pour objectif de déterminer le potentiel des reconstructions itératives statistiques pour réduire au minimum les doses délivrées lors d'examens CT chez l'enfant et le jeune adulte tout en conservant une qualité d'image permettant le diagnostic, ceci afin de proposer des protocoles optimisés.¦L'optimisation d'un protocole d'examen CT nécessite de pouvoir évaluer la dose délivrée et la qualité d'image utile au diagnostic. Alors que la dose est estimée au moyen d'indices CT (CTDIV0| et DLP), ce travail a la particularité d'utiliser deux approches radicalement différentes pour évaluer la qualité d'image. La première approche dite « physique », se base sur le calcul de métriques physiques (SD, MTF, NPS, etc.) mesurées dans des conditions bien définies, le plus souvent sur fantômes. Bien que cette démarche soit limitée car elle n'intègre pas la perception des radiologues, elle permet de caractériser de manière rapide et simple certaines propriétés d'une image. La seconde approche, dite « clinique », est basée sur l'évaluation de structures anatomiques (critères diagnostiques) présentes sur les images de patients. Des radiologues, impliqués dans l'étape d'évaluation, doivent qualifier la qualité des structures d'un point de vue diagnostique en utilisant une échelle de notation simple. Cette approche, lourde à mettre en place, a l'avantage d'être proche du travail du radiologue et peut être considérée comme méthode de référence.¦Parmi les principaux résultats de ce travail, il a été montré que les algorithmes itératifs statistiques étudiés en clinique (ASIR?, VEO?) ont un important potentiel pour réduire la dose au CT (jusqu'à-90%). Cependant, par leur fonctionnement, ils modifient l'apparence de l'image en entraînant un changement de texture qui pourrait affecter la qualité du diagnostic. En comparant les résultats fournis par les approches « clinique » et « physique », il a été montré que ce changement de texture se traduit par une modification du spectre fréquentiel du bruit dont l'analyse permet d'anticiper ou d'éviter une perte diagnostique. Ce travail montre également que l'intégration de ces nouvelles techniques de reconstruction en clinique ne peut se faire de manière simple sur la base de protocoles utilisant des reconstructions classiques. Les conclusions de ce travail ainsi que les outils développés pourront également guider de futures études dans le domaine de la qualité d'image, comme par exemple, l'analyse de textures ou la modélisation d'observateurs pour le CT.¦-¦Computed tomography (CT) is an imaging technique in which interest has been growing since it first began to be used in the early 1970s. In the clinical environment, this imaging system has emerged as the gold standard modality because of its high sensitivity in producing accurate diagnostic images. However, even if a direct benefit to patient healthcare is attributed to CT, the dramatic increase of the number of CT examinations performed has raised concerns about the potential negative effects of ionizing radiation on the population. To insure a benefit - risk that works in favor of a patient, it is important to balance image quality and dose in order to avoid unnecessary patient exposure.¦If this balance is important for adults, it should be an absolute priority for children undergoing CT examinations, especially for patients suffering from diseases requiring several follow-up examinations over the patient's lifetime. Indeed, children and young adults are more sensitive to ionizing radiation and have an extended life span in comparison to adults. For this population, the risk of developing cancer, whose latency period exceeds 20 years, is significantly higher than for adults. Assuming that each patient examination is justified, it then becomes a priority to optimize CT acquisition protocols in order to minimize the delivered dose to the patient. Over the past few years, CT advances have been developing at a rapid pace. Since 2009, new iterative image reconstruction techniques, called statistical iterative reconstructions, have been introduced in order to decrease patient exposure and improve image quality.¦The goal of the present work was to determine the potential of statistical iterative reconstructions to reduce dose as much as possible without compromising image quality and maintain diagnosis of children and young adult examinations.¦The optimization step requires the evaluation of the delivered dose and image quality useful to perform diagnosis. While the dose is estimated using CT indices (CTDIV0| and DLP), the particularity of this research was to use two radically different approaches to evaluate image quality. The first approach, called the "physical approach", computed physical metrics (SD, MTF, NPS, etc.) measured on phantoms in well-known conditions. Although this technique has some limitations because it does not take radiologist perspective into account, it enables the physical characterization of image properties in a simple and timely way. The second approach, called the "clinical approach", was based on the evaluation of anatomical structures (diagnostic criteria) present on patient images. Radiologists, involved in the assessment step, were asked to score image quality of structures for diagnostic purposes using a simple rating scale. This approach is relatively complicated to implement and also time-consuming. Nevertheless, it has the advantage of being very close to the practice of radiologists and is considered as a reference method.¦Primarily, this work revealed that the statistical iterative reconstructions studied in clinic (ASIR? and VECO have a strong potential to reduce CT dose (up to -90%). However, by their mechanisms, they lead to a modification of the image appearance with a change in image texture which may then effect the quality of the diagnosis. By comparing the results of the "clinical" and "physical" approach, it was showed that a change in texture is related to a modification of the noise spectrum bandwidth. The NPS analysis makes possible to anticipate or avoid a decrease in image quality. This project demonstrated that integrating these new statistical iterative reconstruction techniques can be complex and cannot be made on the basis of protocols using conventional reconstructions. The conclusions of this work and the image quality tools developed will be able to guide future studies in the field of image quality as texture analysis or model observers dedicated to CT.

RTOG 0525: A randomized phase iii trial comparing standard adjuvant temozolomide (tmz) with a dose-dense (dd) schedule in newly diagnosed glioblastoma (gbm)

Radiotherapy with concomitant and adjuvant TMZ is the standard of care for newly diagnosed GBM. MGMT methylation status may be an important determinant of treatment response. This trial, conducted by the RTOG, EORTC, and NCCTG, determined if intensified TMZ improves survival (OS) or progression free survival (PFS) in all patients or specific to MGMT status. Eligibility criteria included age . 18 yrs, KPS ≥ 60, and existence of a tissue block with . 1cm2 tumor for prospective MGMT and retrospective molecular analysis. Patients were randomized to Arm 1: standard TMZ (150-200 mg/m2 x 5 d) or Arm 2: dd TMZ (75-100 mg/m2 x 21 d) q 4 wks for 6-12 cycles. Symptom burden, quality of life (QOL), and neurocognition were prospectively and longitudinally assessed in a patient subset. 833 patients were randomized (1173 registered). Inadequate tissue (n ¼ 144) was the most frequent reason for nonrandomization.No statistical difference was observed between Arms 1 and 2 for median OS (16.6, 14.9 mo, p ¼ 0.63), median PFS (5.5, 6.7 mo, p ¼ 0.06), or methylation status. MGMT methylation was associated with improved OS (21.2, 14 mo, p , 0.0001), PFS (8.7, 5.7 mo, p , 0.0001), and treatment response (p ¼ 0.012). Cox modeling identifiedMGMT status and RPA class as significant predictors of OS; treatment arm and radiation technique (EORTC vs. RTOG) were not. There was increased grade ≥ 3 toxicity in Arm 2 (19%, 27%, p ¼ 0.008), which was mostly lymphopenia and fatigue. This study did not demonstrate improved efficacy for dd TMZ for newly diagnosed GBM regardless of methylation status. However, it confirmed the prognostic significance of MGMT methylation in GBM, demonstrated the feasibility of tumor tissue collection, molecular stratification, and collection of patient outcomes in a large transatlantic intergroup trial, thereby establishing a viable clinical trial paradigm. Support: NCI U10 CA 21661 and U10 CA37422.

A novel technique using echocardiography to evaluate venous cannula performance perioperatively in CPB cardiac surgery.

OBJECTIVE: Transthoracic echocardiography (TTE) has been used clinically to disobstruct venous drainage cannula and to optimise placement of venous cannulae in the vena cava but it has never been used to evaluate performance capabilities. Also, little progress has been made in venous cannula design in order to optimise venous return to the heart lung machine. We designed a self-expandable Smartcanula (SC) and analysed its performance capability using echocardiography. METHODS: An epicardial echocardiography probe was placed over the SC or control cannula (CTRL) and a Doppler image was obtained. Mean (V(m)) and maximum (V(max)) velocities, flow and diameter were obtained. Also, pressure drop (DeltaP(CPB)) was obtained between the central venous pressure and inlet to venous reservoir. LDH and Free Hb were also compared in 30 patients. Comparison was made between the two groups using the student's t-test with statistical significance established when p<0.05. RESULTS: Age for the SC and CC groups were 61.6+/-17.6 years and 64.6+/-13.1 years, respectively. Weight was 70.3+/-11.6 kg and 72.8+/-14.4 kg, respectively. BSA was 1.80+/-0.2 m(2) and 1.82+/-0.2 m(2), respectively. CPB times were 114+/-53 min and 108+/-44 min, respectively. Cross-clamp time was 59+/-15 min and 76+/-29 min, respectively (p=NS). Free-Hb was 568+/-142 U/l versus 549+/-271 U/l post-CPB for the SC and CC, respectively (p=NS). LDH was 335+/-73 mg/l versus 354+/-116 mg/l for the SC and CC, respectively (p=NS). V(m) was 89+/-10 cm/s (SC) versus 63+/-3 cm/s (CC), V(max) was 139+/-23 cm/s (SC) versus 93+/-11 cm/s (CC) (both p<0.01). DeltaP(CPB) was 30+/-10 mmHg (SC) versus 43+/-13 mmHg (CC) (p<0.05). A Bland-Altman test showed good agreement between the two devices used concerning flow rate calculations between CPB and TTE (bias 300 ml+/-700 ml standard deviation). CONCLUSIONS: This novel Smartcanula design, due to its self-expanding principle, provides superior flow characteristics compared to classic two stage venous cannula used for adult CPB surgery. No detrimental effects were observed concerning blood damage. Echocardiography was effective in analysing venous cannula performance and velocity patterns.

Aerodynamic drag modeling of alpine skiers performing giant slalom turns.

PURPOSE: Aerodynamic drag plays an important role in performance for athletes practicing sports that involve high-velocity motions. In giant slalom, the skier is continuously changing his/her body posture, and this affects the energy dissipated in aerodynamic drag. It is therefore important to quantify this energy to understand the dynamic behavior of the skier. The aims of this study were to model the aerodynamic drag of alpine skiers in giant slalom simulated conditions and to apply these models in a field experiment to estimate energy dissipated through aerodynamic drag. METHODS: The aerodynamic characteristics of 15 recreational male and female skiers were measured in a wind tunnel while holding nine different skiing-specific postures. The drag and the frontal area were recorded simultaneously for each posture. Four generalized and two individualized models of the drag coefficient were built, using different sets of parameters. These models were subsequently applied in a field study designed to compare the aerodynamic energy losses between a dynamic and a compact skiing technique. RESULTS: The generalized models estimated aerodynamic drag with an accuracy of between 11.00% and 14.28%, and the individualized models estimated aerodynamic drag with an accuracy between 4.52% and 5.30%. The individualized model used for the field study showed that using a dynamic technique led to 10% more aerodynamic drag energy loss than using a compact technique. DISCUSSION: The individualized models were capable of discriminating different techniques performed by advanced skiers and seemed more accurate than the generalized models. The models presented here offer a simple yet accurate method to estimate the aerodynamic drag acting upon alpine skiers while rapidly moving through the range of positions typical to turning technique.

Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling

The interpretation of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all crossloadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores.

Statistical discrimination of black gel pen inks analysed by laser desorption/ionization mass spectrometry

Pearson correlation coefficients were applied for the objective comparison of 30 black gel pen inks analysed by laser desorption ionization mass spectrometry (LDI-MS). The mass spectra were obtained for ink lines directly on paper using positive and negative ion modes at several laser intensities. This methodology has the advantage of taking into account the reproducibility of the results as well as the variability between spectra of different pens. A differentiation threshold could thus be selected in order to avoid the risk of false differentiation. Combining results from positive and negative mode yielded a discriminating power up to 85%, which was better than the one obtained previously with other optical comparison methodologies. The technique also allowed discriminating between pens from the same brand.

Multi-level modeling of aspects associated with poor mental health in a sample of prehospital emergency professionals.

BACKGROUND: The goal of this paper is to investigate the respective influence of work characteristics, the effort-reward ratio, and overcommitment on the poor mental health of out-of-hospital care providers. METHODS: 333 out-of-hospital care providers answered a questionnaire that included queries on mental health (GHQ-12), demographics, health-related information and work characteristics, questions from the Effort-Reward Imbalance Questionnaire, and items about overcommitment. A two-level multiple regression was performed between mental health (the dependent variable) and the effort-reward ratio, the overcommitment score, weekly number of interventions, percentage of non-prehospital transport of patients out of total missions, gender, and age. Participants were first-level units, and ambulance services were second-level units. We also shadowed ambulance personnel for a total of 416 hr. RESULTS: With cutoff points of 2/3 and 3/4 positive answers on the GHQ-12, the percentages of potential cases with poor mental health were 20% and 15%, respectively. The effort-reward ratio was associated with poor mental health (P < 0.001), irrespective of age or gender. Overcommitment was associated with poor mental health; this association was stronger in women (β = 0.054) than in men (β = 0.020). The percentage of prehospital missions out of total missions was only associated with poor mental health at the individual level. CONCLUSIONS: Emergency medical services should pay attention to the way employees perceive their efforts and the rewarding aspects of their work: an imbalance of those aspects is associated with poor mental health. Low perceived esteem appeared particularly associated with poor mental health. This suggests that supervisors of emergency medical services should enhance the value of their employees' work. Employees with overcommitment should also receive appropriate consideration. Preventive measures should target individual perceptions of effort and reward in order to improve mental health in prehospital care providers.

Cost-effective experimental design to support modeling of concentration-response functions

Modeling concentration-response function became extremely popular in ecotoxicology during the last decade. Indeed, modeling allows determining the total response pattern of a given substance. However, reliable modeling is consuming in term of data, which is in contradiction with the current trend in ecotoxicology, which aims to reduce, for cost and ethical reasons, the number of data produced during an experiment. It is therefore crucial to determine experimental design in a cost-effective manner. In this paper, we propose to use the theory of locally D-optimal designs to determine the set of concentrations to be tested so that the parameters of the concentration-response function can be estimated with high precision. We illustrated this approach by determining the locally D-optimal designs to estimate the toxicity of the herbicide dinoseb on daphnids and algae. The results show that the number of concentrations to be tested is often equal to the number of parameters and often related to the their meaning, i.e. they are located close to the parameters. Furthermore, the results show that the locally D-optimal design often has the minimal number of support points and is not much sensitive to small changes in nominal values of the parameters. In order to reduce the experimental cost and the use of test organisms, especially in case of long-term studies, reliable nominal values may therefore be fixed based on prior knowledge and literature research instead of on preliminary experiments