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PubMed1996

Intermediate-term earthquake prediction.

An earthquake of magnitude M and linear source dimension L(M) is preceded within a few years by certain patterns of seismicity in the magnitude range down to about (M - 3) in an area of linear dimension about 5L-10L. Prediction algorithms based on such patterns may allow one to predict approximately 80% of strong earthquakes with alarms occupying altogether 20-30% of the time-space considered. An area of alarm can be narrowed down to 2L-3L when observations include lower magnitudes, down to about (M - 4). In spite of their limited accuracy, such predictions open a possibility to prevent considerable damage. The following findings may provide for further development of prediction methods: (i) long-range correlations in fault system dynamics and accordingly large size of the areas over which different observed fields could be averaged and analyzed jointly, (ii) specific symptoms of an approaching strong earthquake, (iii) the partial similarity of these symptoms worldwide, (iv) the fact that some of them are not Earth specific: we probably encountered in seismicity the symptoms of instability common for a wide class of nonlinear systems.

Journal Article↗
PubMed2006

Inverse retinotopy: inferring the visual content of images from brain activation patterns.

Traditional inference in neuroimaging consists in describing brain activations elicited and modulated by different kinds of stimuli. Recently, however, paradigms have been studied in which the converse operation is performed, thus inferring behavioral or mental states associated with activation images. Here, we use the well-known retinotopy of the visual cortex to infer the visual content of real or imaginary scenes from the brain activation patterns that they elicit. We present two decoding algorithms: an explicit technique, based on the current knowledge of the retinotopic structure of the visual areas, and an implicit technique, based on supervised classifiers. Both algorithms predicted the stimulus identity with significant accuracy. Furthermore, we extend this principle to mental imagery data: in five data sets, our algorithms could reconstruct and predict with significant accuracy a pattern imagined by the subjects.

Humans↗
PubMed2001

Predicting tissue outcome in acute human cerebral ischemia using combined diffusion- and perfusion-weighted MR imaging.

BACKGROUND AND PURPOSE: Tissue signatures from acute MR imaging of the brain may be able to categorize physiological status and thereby assist clinical decision making. We designed and analyzed statistical algorithms to evaluate the risk of infarction for each voxel of tissue using acute human functional MRI. METHODS: Diffusion-weighted MR images (DWI) and perfusion-weighted MR images (PWI) from acute stroke patients scanned within 12 hours of symptom onset were retrospectively studied and used to develop thresholding and generalized linear model (GLM) algorithms predicting tissue outcome as determined by follow-up MRI. The performances of the algorithms were evaluated for each patient by using receiver operating characteristic curves. RESULTS: At their optimal operating points, thresholding algorithms combining DWI and PWI provided 66% sensitivity and 83% specificity, and GLM algorithms combining DWI and PWI predicted with 66% sensitivity and 84% specificity voxels that proceeded to infarct. Thresholding algorithms that combined DWI and PWI provided significant improvement to algorithms that utilized DWI alone (P=0.02) but no significant improvement over algorithms utilizing PWI alone (P=0.21). GLM algorithms that combined DWI and PWI showed significant improvement over algorithms that used only DWI (P=0.02) or PWI (P=0.04). The performances of thresholding and GLM algorithms were comparable (P>0.2). CONCLUSIONS: Algorithms that combine acute DWI and PWI can assess the risk of infarction with higher specificity and sensitivity than algorithms that use DWI or PWI individually. Methods for quantitatively assessing the risk of infarction on a voxel-by-voxel basis show promise as techniques for investigating the natural spatial evolution of ischemic damage in humans.

Acute Disease↗
PubMed2000

Prediction of protein subcellular locations by incorporating quasi-sequence-order effect.

How to incorporate the sequence order effect is a key and logical step for improving the prediction quality of protein subcellular location, but meanwhile it is a very difficult problem as well. This is because the number of possible sequence order patterns in proteins is extremely large, which has posed a formidable barrier to construct an effective training data set for statistical treatment based on the current knowledge. That is why most of the existing prediction algorithms are operated based on the amino-acid composition alone. In this paper, based on the physicochemical distance between amino acids, a set of sequence-order-coupling numbers was introduced to reflect the sequence order effect, or in a rigorous term, the quasi-sequence-order effect. Furthermore, the covariant discriminant algorithm by Chou and Elrod (Protein Eng. 12, 107-118, 1999) developed recently was augmented to allow the prediction performed by using the input of both the sequence-order-coupling numbers and amino-acid composition. A remarkable improvement was observed in the prediction quality using the augmented covariant discriminant algorithm. The approach described here represents one promising step forward in the efforts of incorporating sequence order effect in protein subcellular location prediction. It is anticipated that the current approach may also have a series of impacts on the prediction of other protein features by statistical approaches.

Algorithms↗
PubMed1982

Structural prediction of membrane-bound proteins.

A prediction algorithm based on physical characteristics of the twenty amino acids and refined by comparison to the proposed bacteriorhodopsin structure was devised to delineate likely membrane-buried regions in the primary sequences of proteins known to interact with the lipid bilayer. Application of the method to the sequence of the carboxyl terminal one-third of bovine rhodopsin predicted a membrane-buried helical hairpin structure. With the use of lipid-buried segments in bacteriorhodopsin as well as regions predicted by the algorithm in other membrane-bound proteins, a hierarchical ranking of the twenty amino acids in their preferences to be in lipid contact was calculated. A helical wheel analysis of the predicted regions suggests which helical faces are within the protein interior and which are in contact with the lipid bilayer.

Amino Acid Sequence↗
PubMed1997

Sexually transmitted disease among married Zambian women: the role of male and female sexual behaviour in prevention and management.

OBJECTIVES: Few studies have evaluated the relation between male and female sexual behaviour and STD among married African women. The objectives of this study were to identify male and female sexual behaviour associated with female STD, and to explore whether incorporating male and female sexual behaviour and male symptoms can improve algorithms for STD management in married African women. METHODS: 99 married couples with one symptomatic member (58 males, 41 females) attending an STD clinic in Lusaka, Zambia were interviewed separately about sexual and contraceptive behaviour, and had physical examinations. Diagnostic tests for Neisseria gonorrhoeae (GC), Trichomonas vaginalis (TV), and HIV were performed. Bivariate and multivariate odds ratios for the association between sexual behaviour and STD were calculated. Predictive algorithms based on current Zambian guidelines for management of STD in women were created. RESULTS: Among women at baseline, 10% were positive for GC, 14% for TV, 52% for HIV. Female alcohol use before sex, a male's paying for sex, and a couple's having sex unprotected by condoms or spermicides were associated with female STD. Incorporation of these behaviours along with symptoms of urethral discharge and dysuria among husbands increased the predictive ability of algorithms for management of STD in women. CONCLUSIONS: The addition of male and female sexual behaviour and male STD symptoms to diagnostic algorithms for female STD should be explored in other settings. Both husbands' and wives' behaviour independently predict STD in these women; risk reduction programmes should target both men's and women's sexual behaviour.

Adult↗
PubMed2001

Morphological characteristics of P waves during selective pulmonary vein pacing.

OBJECTIVES: We sought to assess the value of 12-lead electrocardiogram (ECG) P-wave morphology to recognize the paced pulmonary vein (PV). BACKGROUND: Prediction of arrhythmogenic PVs producing ectopy or initiating atrial fibrillation (AF) using 12-lead ECG may facilitate curative ablation. METHODS: In 30 patients P-wave configurations were studied during sinus rhythm and during pacing at six sites from the four PVs: top and bottom of each superior PV and both inferior PVs. The P-wave amplitude, duration and morphology were assessed, and predictive accuracies were calculated for the most significant parameters. An algorithm predicting the paced PV was developed and prospectively evaluated in a different population of 20 patients. RESULTS; Three criteria were used to distinguish right from left PV: 1) a positive P-wave in lead aVL and the amplitude of P-wave in lead I > or =50 microV indicated right PV origin (specificity 100% and 97%, respectively); 2) a notched P-wave in lead II was a predictor of left PV origin (specificity 95%); and 3) the amplitude ratio of lead III/II and the duration of positivity in lead V(1) were also helpful in distinguishing left versus right PV origin. In addition, superior PVs could be distinguished from inferior according to the amplitude in lead II (> or =100 microV). In prospective evaluation, an algorithm based on the above four criteria identified 93% of left versus right PV and totally 79% of the specific PVs paced. CONCLUSIONS: Pacing from the different PVs produced a P-wave with distinctive characteristics that could be used as criteria in an algorithm to identify the PV of origin with an accuracy of 79%.

Aged↗
PubMed1986

An algorithm for secondary structure determination in proteins based on sequence similarity.

A secondary structure prediction algorithm is proposed on the hypothesis that short homologous sequences of amino acids have the same secondary structure tendencies. Comparisons are made with the secondary structure assignments of Kabsch and Sander from X-ray data [(1983) Biopolymers 22, 2577-2637] and an empirically determined similarity matrix which assigns a sequence similarity score between any two sequences of 7 residues in length. This similarity matrix differs in many respects from that of the Dayhoff substitution matrix [(1978) in: Atlas of Protein Sequence and Structure, (Dayhoff, M.O. ed). vol. 5. suppl. 3, pp. 353-358, National Biochemical Research Foundation, Washington, DC]. This homologue method had a prediction accuracy of 62.2% over 3 states for 61 proteins and 63.6% for a new set of 7 proteins not in the original data base.

Amino Acid Sequence↗
PubMed2025

Study research protocol for Phenome India-CSIR Health Cohort Knowledgebase: A prospective multi-modal follow-up study on a nationwide employee cohort.

Predicting individual health trajectories based on risk scores can help formulate effective preventive strategies for diseases and their complications. Currently, most risk prediction algorithms rely on epidemiological data from the Caucasian population, which often do not translate well to the Indian population due to ethnic diversity, differing dietary and lifestyle habits, and unique risk profiles. In this multi-center prospective longitudinal study conducted across India, we aim to address these challenges by developing clinically relevant risk prediction scores for cardio-metabolic diseases specifically tailored to the Indian population. India, which accounts for nearly 18% of the global population, also has a significant diaspora worldwide. This program targets longitudinal collection and bio-banking of samples from over 10 000 employees both working and retirees of the Council of Scientific and Industrial Research and their spouses, with baseline sample collection already completed. During the baseline collection, we gathered multi-parametric data including clinical questionnaires, lifestyle and dietary habits, anthropometric parameters, lung function assessments, liver elastography by Fibroscan, electrocardiogram readings, biochemical data, and molecular assays, including but not limited to genomics, plasma proteomics, metabolomics, and fecal microbiome analysis. In addition to exploring associations between these parameters and their cardio-metabolic outcomes, we plan to employ artificial intelligence algorithms to develop predictive models for phenotypic conditions. This study could pave the way for precision medicine tailored to the Indian population, particularly for the middle-income strata, and help refine the normative values for health and disease indicators in India.

cardio-metabolic↗
PubMed2002

DOLOP--database of bacterial lipoproteins.

UNLABELLED: Bacterial lipoproteins and lipid modification are gaining importance owing to their essential nature, roles in pathogenesis and interesting commercial applications. We have created an exclusive knowledge base for bacterial lipoproteins by processing information from 510 entries to provide a list of 199 distinct lipoproteins with relevant links to molecular details. Features include functional classification, predictive algorithm for query sequences, primary sequence analysis and lists of predicted lipoproteins from 43 completed bacterial genomes along with interactive information exchange facility. AVAILABILITY: The website called Database Of bacterial LipOProteins (DOLOP) is available at http://www.mrc-lmb.cam.ac.uk/genomes/dolop along with additional information on the biosynthetic pathway, supplementary material and other related figures.

Algorithms↗
PubMed2005

A support vector machine-based method for predicting the propensity of a protein to be soluble or to form inclusion body on overexpression in Escherichia coli.

MOTIVATION: Inclusion body formation has been a major deterrent for overexpression studies since a large number of proteins form insoluble inclusion bodies when overexpressed in Escherichia coli. The formation of inclusion bodies is known to be an outcome of improper protein folding; thus the composition and arrangement of amino acids in the proteins would be a major influencing factor in deciding its aggregation propensity. There is a significant need for a prediction algorithm that would enable the rational identification of both mutants and also the ideal protein candidates for mutations that would confer higher solubility-on-overexpression instead of the presently used trial-and-error procedures. RESULTS: Six physicochemical properties together with residue and dipeptide-compositions have been used to develop a support vector machine-based classifier to predict the overexpression status in E.coli. The prediction accuracy is approximately 72% suggesting that it performs reasonably well in predicting the propensity of a protein to be soluble or to form inclusion bodies. The algorithm could also correctly predict the change in solubility for most of the point mutations reported in literature. This algorithm can be a useful tool in screening protein libraries to identify soluble variants of proteins.

Algorithms↗
PubMed2002

Fold prediction of helical proteins using torsion angle dynamics and predicted restraints.

We describe a procedure for predicting the tertiary folds of alpha-helical proteins from their primary sequences. The central component of the procedure is a method for predicting interhelical contacts that is based on a helix-packing model. Instead of predicting the individual contacts, our method attempts to identify the entire patch of contacts that involve residues regularly spaced in the sequences. We use this component to glue together two powerful existing methods: a secondary structure prediction program, whose output serves as the input to the contact prediction algorithm, and the tortion angle dynamics program, which uses the predicted tertiary contacts and secondary structural states to assemble three-dimensional structures. In the final step, the procedure uses the initial set of simulated structures to refine the predicted contacts for a new round of structure calculation. When tested against 24 small to medium-sized proteins representing a wide range of helical folds, the completely automated procedure is able to generate native-like models within a limited number of trials consistently.

Algorithms↗
PubMed2005

Most nuclear systemic autoantigens are extremely disordered proteins: implications for the etiology of systemic autoimmunity.

Patients with systemic autoimmune diseases usually produce high levels of antibodies to self-antigens (autoantigens). The repertoire of common autoantigens is remarkably limited, yet no readily understandable shared thread links these apparently diverse proteins. Using computer prediction algorithms, we have found that most nuclear systemic autoantigens are predicted to contain long regions of extreme structural disorder. Such disordered regions would generally make poor B cell epitopes and are predicted to be under-represented as potential T cell epitopes. Consideration of the potential role of protein disorder may give novel insights into the possible role of molecular mimicry in the pathogenesis of autoimmunity. The recognition of extreme autoantigen protein disorder has led us to an explicit model of epitope spreading that explains many of the paradoxical aspects of autoimmunity - in particular, the difficulty in identifying autoantigen-specific helper T cells that might collaborate with the B cells activated in systemic autoimmunity. The model also explains the experimentally observed breakdown of major histocompatibility complex (MHC) class specificity in peptides associated with the MHC II proteins of activated autoimmune B cells, and sheds light on the selection of particular T cell epitopes in autoimmunity. Finally, the model helps to rationalize the relative rarity of clinically significant autoimmunity despite the prevalence of low specificity/low avidity autoantibodies in normal individuals.

Algorithms↗
PubMed2003

In silico analysis reveals substantial variability in the gene contents of the gamma proteobacteria LexA-regulon.

MOTIVATION: Motif-prediction algorithm capabilities for the analysis of bacterial regulatory networks and the prediction of new regulatory sites can be greatly enhanced by the use of comparative genomics approaches. In this study, we make use of a consensus-building algorithm and comparative genomics to conduct an in-depth analysis of the LexA-regulon of gamma proteobacteria, and we use the inferred results to study the evolution of this regulatory network and to examine the usefulness of the control sequences and gene contents of regulons in phylogenetic analysis. RESULTS: We show, for the first time, the substantial heterogeneity that the LexA-regulon of gamma proteobacteria displays in terms of gene content and we analyze possible branching points in its evolution. We also demonstrate the feasibility of using regulon-related information to derive sound phylogenetic inferences. AVAILABILITY: Complementary analysis data and both the source code and the Windows-executable files of the consensus-building software are available at http://www.cnm.es/~ivan/RCGScanner/

Algorithms↗
PubMed1998

Assessment of conformational parameters as predictors of limited proteolytic sites in native protein structures.

Despite the importance of limited proteolysis in biological systems it is often difficult to rationalize why a proteinase hydrolyses a particular bond, given a simple sequence specificity alone. Understanding of the structural properties limiting the proteolysis represents a first step on the pathway to control and manipulation of this phenomena. An expanded set of nick-sites in proteins of known tertiary structure, cut by both narrow and broad specificity proteinases, has been generated yielding a robust data set of strictly limited sites. A critical evaluation of an expanded set of conformational parameters revealed a strong correlation with limited proteolytic sites, although they are only modest predictors in isolation. The overall predictive power is significantly improved when the conformational parameters are combined in a weighted predictive scheme that permits their relative importance to be compared via a Metropolis search protocol. A subset of the parameters performs equally well demonstrating the key determinants of susceptibility. The derived predictive algorithm has been made available via the internet. Its utility for predicting other surface-correlated features is also discussed.

Algorithms↗
PubMed2005

SNEP: SNP-derived epitope prediction program for minor H antigens.

The single nucleotide polymorphism (SNP)-derived Epitope Prediction program (SNEP) is now available to the public. It predicts minor histocompatibility antigens (miHAgs), which are T-cell epitopes containing polymorphic spots, from proteins listed in the SWISS-PROT database. SNEP recognizes polymorphisms (termed VARIANT or CONFLICT in SWISS-PROT) and predicts potential T-cell epitopes within a chosen distance around the polymorphic residue. The prediction algorithm is based on the SYFPEITHI T-cell epitope prediction program. SNEP is able to search for proteins according to their accession numbers, sequence stretches or gene names, for example. The predictions are available for several human leucocyte antigen class I and class II allelic products, which allow for a rapid and precise evaluation of potential miHAgs within polymorphic antigens.

Amino Acid Sequence↗
PubMed1997

Antigen processing by proteasomes: insights into the molecular basis of crypticity.

Eight to eleven amino acid residues are the sizes of predominant peptides found to be associated with MHC class I molecules. Proteasomes have been implicated in antigen processing and generation of such peptides. Advanced methodologies in peptide elution together with sequence determination have led to the characterisation of MHC class I binding motifs. More recently, screening of random peptide phage display libraries and synthetic combinatorial peptide libraries have also been successfully used. This has led to the development and use of predictive algorithms to screen antigens for potential CTL epitopes. Not all predicted epitopes will be generated in vivo and the emerging picture suggests differential presentation of predicted CTL epitopes ranging from cryptic to immunodominant. The scope of this review is to discuss antigen processing by proteasomes, and to put forward a hypothesis that the molecular basis of immunogenicity can be a function of proteasomal processing. This may explain how pathogens and tumours are able to escape immunosurveillance by altering sequences required by proteasomes for epitope generation.

Antigen Presentation↗
PubMed1993

Identification of B-cell epitopes on the S4 subunit of pertussis toxin.

The main purpose of the present study was to identify B-cell epitopes on the S4 subunit of pertussis toxin (PT) by the synthetic peptide approach. Two strategies were followed: (i) screening of two series of overlapping peptides (12- and 25-residue peptides) covering the entire S4 sequence by a panel of murine monoclonal anti-PT antibodies and various polyclonal anti-PT antisera in an enzyme-linked immunosorbent assay (ELISA), and (ii) analysis of the S4 amino acid sequence by a predictive algorithm followed by synthesis and immunization of mice with the predicted peptides coupled to diphtheria toxoid. The anti-peptide conjugate antisera were tested in an ELISA for cross-reactivity with native PT, B oligomer, and S4. Screening of the free peptides in an ELISA by the PT antisera indicated the presence of six B-cell epitope-containing domains covered by residues 18 to 32, 33 to 46, 39 to 52, 51 to 65, 71 to 84, and 91 to 106. None of the peptides, however, were recognized by the monoclonal anti-PT antibodies in an ELISA. Immunization with six computer-predicted peptides (B1 to B6) and three potential T-cell epitopes (T1 to T3) gave rise to very high antibody responses towards the homologous conjugates. With the exception of the anti-T1/diphtheria toxoid antisera, all anti-peptide conjugate antisera cross-reacted with PT in an ELISA at different levels. None of these anti-peptide conjugate antisera, however, showed any PT-neutralizing effect as measured by the Chinese hamster ovary cell assay and the leukocytosis-promoting activity test. The results of the present study suggest that discontinuous epitopes are predominant in the S4 subunit of native PT.

Amino Acid Sequence↗