Biomedical subjects

Michael I Jordan

Publications and source records attributed to Michael I Jordan.

14 recordsLinked to original sources

PubMed2005

Protein molecular function prediction by Bayesian phylogenomics.

We present a statistical graphical model to infer specific molecular function for unannotated protein sequences using homology. Based on phylogenomic principles, SIFTER (Statistical Inference of Function Through Evolutionary Relationships) accurately predicts molecular function for members of a protein family given a reconciled phylogeny and available function annotations, even when the data are sparse or noisy. Our method produced specific and consistent molecular function predictions across 100 Pfam families in comparison to the Gene Ontology annotation database, BLAST, GOtcha, and Orthostrapper. We performed a more detailed exploration of functional predictions on the adenosine-5'-monophosphate/adenosine deaminase family and the lactate/malate dehydrogenase family, in the former case comparing the predictions against a gold standard set of published functional characterizations. Given function annotations for 3% of the proteins in the deaminase family, SIFTER achieves 96% accuracy in predicting molecular function for experimentally characterized proteins as reported in the literature. The accuracy of SIFTER on this dataset is a significant improvement over other currently available methods such as BLAST (75%), GeneQuiz (64%), GOtcha (89%), and Orthostrapper (11%). We also experimentally characterized the adenosine deaminase from Plasmodium falciparum, confirming SIFTER's prediction. The results illustrate the predictive power of exploiting a statistical model of function evolution in phylogenomic problems. A software implementation of SIFTER is available from the authors.

Adenosine Deaminase↗

PubMed2005

Genome-wide requirements for resistance to functionally distinct DNA-damaging agents.

The mechanistic and therapeutic differences in the cellular response to DNA-damaging compounds are not completely understood, despite intense study. To expand our knowledge of DNA damage, we assayed the effects of 12 closely related DNA-damaging agents on the complete pool of approximately 4,700 barcoded homozygous deletion strains of Saccharomyces cerevisiae. In our protocol, deletion strains are pooled together and grown competitively in the presence of compound. Relative strain sensitivity is determined by hybridization of PCR-amplified barcodes to an oligonucleotide array carrying the barcode complements. These screens identified genes in well-characterized DNA-damage-response pathways as well as genes whose role in the DNA-damage response had not been previously established. High-throughput individual growth analysis was used to independently confirm microarray results. Each compound produced a unique genome-wide profile. Analysis of these data allowed us to determine the relative importance of DNA-repair modules for resistance to each of the 12 profiled compounds. Clustering the data for 12 distinct compounds uncovered both known and novel functional interactions that comprise the DNA-damage response and allowed us to define the genetic determinants required for repair of interstrand cross-links. Further genetic analysis allowed determination of epistasis for one of these functional groups.

Antifungal Agents↗

PubMed2005

A latent variable model for chemogenomic profiling.

MOTIVATION: In haploinsufficiency profiling data, pleiotropic genes are often misclassified by clustering algorithms that impose the constraint that a gene or experiment belong to only one cluster. We have developed a general probabilistic model that clusters genes and experiments without requiring that a given gene or drug only appear in one cluster. The model also incorporates the functional annotation of known genes to guide the clustering procedure. RESULTS: We applied our model to the clustering of 79 chemogenomic experiments in yeast. Known pleiotropic genes PDR5 and MAL11 are more accurately represented by the model than by a clustering procedure that requires genes to belong to a single cluster. Drugs such as miconazole and fenpropimorph that have different targets but similar off-target genes are clustered more accurately by the model-based framework. We show that this model is useful for summarizing the relationship among treatments and genes affected by those treatments in a compendium of microarray profiles. AVAILABILITY: Supplementary information and computer code at http://genomics.lbl.gov/llda.

Computer Simulation↗

PubMed2005

Subtree power analysis and species selection for comparative genomics.

Sequence comparison across multiple organisms aids in the detection of regions under selection. However, resource limitations require a prioritization of genomes to be sequenced. This prioritization should be grounded in two considerations: the lineal scope encompassing the biological phenomena of interest, and the optimal species within that scope for detecting functional elements. We introduce a statistical framework for optimal species subset selection, based on maximizing power to detect conserved sites. Analysis of a phylogenetic star topology shows theoretically that the optimal species subset is not in general the most evolutionarily diverged subset. We then demonstrate this finding empirically in a study of vertebrate species. Our results suggest that marsupials are prime sequencing candidates.

Animals↗

PubMed2005

Lessons from Escherichia coli genes similarly regulated in response to nitrogen and sulfur limitation.

We previously characterized nutrient-specific transcriptional changes in Escherichia coli upon limitation of nitrogen (N) or sulfur (S). These global homeostatic responses presumably minimize the slowing of growth under a particular condition. Here, we characterize responses to slow growth per se that are not nutrient-specific. The latter help to coordinate the slowing of growth, and in the case of down-regulated genes, to conserve scarce N or S for other purposes. Three effects were particularly striking. First, although many genes under control of the stationary phase sigma factor RpoS were induced and were apparently required under S-limiting conditions, one or more was inhibitory under N-limiting conditions, or RpoS itself was inhibitory. RpoS was, however, universally required during nutrient downshifts. Second, limitation for N and S greatly decreased expression of genes required for synthesis of flagella and chemotaxis, and the motility of E. coli was decreased. Finally, unlike the response of all other met genes, transcription of metE was decreased under S- and N-limiting conditions. The metE product, a methionine synthase, is one of the most abundant proteins in E. coli grown aerobically in minimal medium. Responses of metE to S and N limitation pointed to an interesting physiological rationale for the regulatory subcircuit controlled by the methionine activator MetR.

Bacterial Proteins↗

PubMed2005

Sulfur and nitrogen limitation in Escherichia coli K-12: specific homeostatic responses.

We determined global transcriptional responses of Escherichia coli K-12 to sulfur (S)- or nitrogen (N)-limited growth in adapted batch cultures and cultures subjected to nutrient shifts. Using two limitations helped to distinguish between nutrient-specific changes in mRNA levels and common changes related to the growth rate. Both homeostatic and slow growth responses were amplified upon shifts. This made detection of these responses more reliable and increased the number of genes that were differentially expressed. We analyzed microarray data in several ways: by determining expression changes after use of a statistical normalization algorithm, by hierarchical and k-means clustering, and by visual inspection of aligned genome images. Using these tools, we confirmed known homeostatic responses to global S limitation, which are controlled by the activators CysB and Cbl, and found that S limitation propagated into methionine metabolism, synthesis of FeS clusters, and oxidative stress. In addition, we identified several open reading frames likely to respond specifically to S availability. As predicted from the fact that the ddp operon is activated by NtrC, synthesis of cross-links between diaminopimelate residues in the murein layer was increased under N-limiting conditions, as was the proportion of tripeptides. Both of these effects may allow increased scavenging of N from the dipeptide D-alanine-D-alanine, the substrate of the Ddp system.

Cluster Analysis↗

PubMed2004

A statistical framework for genomic data fusion.

MOTIVATION: During the past decade, the new focus on genomics has highlighted a particular challenge: to integrate the different views of the genome that are provided by various types of experimental data. RESULTS: This paper describes a computational framework for integrating and drawing inferences from a collection of genome-wide measurements. Each dataset is represented via a kernel function, which defines generalized similarity relationships between pairs of entities, such as genes or proteins. The kernel representation is both flexible and efficient, and can be applied to many different types of data. Furthermore, kernel functions derived from different types of data can be combined in a straightforward fashion. Recent advances in the theory of kernel methods have provided efficient algorithms to perform such combinations in a way that minimizes a statistical loss function. These methods exploit semidefinite programming techniques to reduce the problem of finding optimizing kernel combinations to a convex optimization problem. Computational experiments performed using yeast genome-wide datasets, including amino acid sequences, hydropathy profiles, gene expression data and known protein-protein interactions, demonstrate the utility of this approach. A statistical learning algorithm trained from all of these data to recognize particular classes of proteins--membrane proteins and ribosomal proteins--performs significantly better than the same algorithm trained on any single type of data. AVAILABILITY: Supplementary data at http://noble.gs.washington.edu/proj/sdp-svm

Algorithms↗

PubMed2004

Multiple-sequence functional annotation and the generalized hidden Markov phylogeny.

MOTIVATION: Phylogenetic shadowing is a comparative genomics principle that allows for the discovery of conserved regions in sequences from multiple closely related organisms. We develop a formal probabilistic framework for combining phylogenetic shadowing with feature-based functional annotation methods. The resulting model, a generalized hidden Markov phylogeny (GHMP), applies to a variety of situations where functional regions are to be inferred from evolutionary constraints. RESULTS: We show how GHMPs can be used to predict complete shared gene structures in multiple primate sequences. We also describe shadower, our implementation of such a prediction system. We find that shadower outperforms previously reported ab initio gene finders, including comparative human-mouse approaches, on a small sample of diverse exonic regions. Finally, we report on an empirical analysis of shadower's performance which reveals that as few as five well-chosen species may suffice to attain maximal sensitivity and specificity in exon demarcation. AVAILABILITY: A Web server is available at http://bonaire.lbl.gov/shadower

Algorithms↗

PubMed2004

Chemogenomic profiling: identifying the functional interactions of small molecules in yeast.

We demonstrate the efficacy of a genome-wide protocol in yeast that allows the identification of those gene products that functionally interact with small molecules and result in the inhibition of cellular proliferation. Here we present results from screening 10 diverse compounds in 80 genome-wide experiments against the complete collection of heterozygous yeast deletion strains. These compounds include anticancer and antifungal agents, statins, alverine citrate, and dyclonine. In several cases, we identified previously known interactions; furthermore, in each case, our analysis revealed novel cellular interactions, even when the relationship between a compound and its cellular target had been well established. In addition, we identified a chemical core structure shared among three therapeutically distinct compounds that inhibit the ERG24 heterozygous deletion strain, demonstrating that cells may respond similarly to compounds of related structure. The ability to identify on-and-off target effects in vivo is fundamental to understanding the cellular response to small-molecule perturbants.

Antifungal Agents↗

PubMed2004

Logos: a modular bayesian model for de novo motif detection.

The complexity of the global organization and internal structure of motifs in higher eukaryotic organisms raises significant challenges for motif detection techniques. To achieve successful de novo motif detection, it is necessary to model the complex dependencies within and among motifs and to incorporate biological prior knowledge. In this paper, we present LOGOS, an integrated LOcal and GlObal motif Sequence model for biopolymer sequences, which provides a principled framework for developing, modularizing, extending and computing expressive motif models for complex biopolymer sequence analysis. LOGOS consists of two interacting submodels: HMDM, a local alignment model capturing biological prior knowledge and positional dependency within the motif local structure; and HMM, a global motif distribution model modeling frequencies and dependencies of motif occurrences. Model parameters can be fit using training motifs within an empirical Bayesian framework. A variational EM algorithm is developed for de novo motif detection. LOGOS improves over existing models that ignore biological priors and dependencies in motif structures and motif occurrences, and demonstrates superior performance on both semi-realistic test data and cis-regulatory sequences from yeast and Drosophila genomes with regard to sensitivity, specificity, flexibility and extensibility.

Algorithms↗

PubMed2003

Toward a protein profile of Escherichia coli: comparison to its transcription profile.

High-pressure liquid chromatography-tandem mass spectrometry was used to obtain a protein profile of Escherichia coli strain MG1655 grown in minimal medium with glycerol as the carbon source. By using cell lysate from only 3 x 108 cells, at least four different tryptic peptides were detected for each of 404 proteins in a short 4-h experiment. At least one peptide with a high reliability score was detected for 986 proteins. Because membrane proteins were underrepresented, a second experiment was performed with a preparation enriched in membranes. An additional 161 proteins were detected, of which from half to two-thirds were membrane proteins. Overall, 1,147 different E. coli proteins were identified, almost 4 times as many as had been identified previously by using other tools. The protein list was compared with the transcription profile obtained on Affymetrix GeneChips. Expression of 1,113 (97%) of the genes whose protein products were found was detected at the mRNA level. The arithmetic mean mRNA signal intensity for these genes was 3-fold higher than that for all 4,300 protein-coding genes of E. coli. Thus, GeneChip data confirmed the high reliability of the protein list, which contains about one-fourth of the proteins of E. coli. Detection of even those membrane proteins and proteins of undefined function that are encoded by the same operons (transcriptional units) encoding proteins on the list remained low.

Cell Membrane↗

PubMed2003

LOGOS: a modular Bayesian model for de novo motif detection.

The complexity of the global organization and internal structures of motifs in higher eukaryotic organisms raises significant challenges for motif detection techniques. To achieve successful de novo motif detection it is necessary to model the complex dependencies within and among motifs and incorporate biological prior knowledge. In this paper, we present LOGOS, an integrated LOcal and GlObal motif Sequence model for biopolymer sequences, which provides a principled framework for developing, modularizing, extending and computing expressive motif models for complex biopolymer sequence analysis. LOGOS consists of two interacting submodels: HMDM, a local alignment model capturing biological prior knowledge and positional dependence within the motif local structure; and HMM, a global motif distribution model modeling frequencies and dependencies of motif occurrences. Model parameters can be fit using training motifs within an empirical Bayesian framework. A variational EM algorithm is developed for de novo motif detection. LOGOS improves over existing models that ignore biological priors and dependencies in motif structures and motif occurrences, and demonstrates superior performance on both semi-realistic test data and cis-regulatory sequences from yeast and Drosophila sequences with regard to sensitivity, specificity, flexibility and extensibility.

Algorithms↗

PubMed2002

Optimal feedback control as a theory of motor coordination.

A central problem in motor control is understanding how the many biomechanical degrees of freedom are coordinated to achieve a common goal. An especially puzzling aspect of coordination is that behavioral goals are achieved reliably and repeatedly with movements rarely reproducible in their detail. Existing theoretical frameworks emphasize either goal achievement or the richness of motor variability, but fail to reconcile the two. Here we propose an alternative theory based on stochastic optimal feedback control. We show that the optimal strategy in the face of uncertainty is to allow variability in redundant (task-irrelevant) dimensions. This strategy does not enforce a desired trajectory, but uses feedback more intelligently, correcting only those deviations that interfere with task goals. From this framework, task-constrained variability, goal-directed corrections, motor synergies, controlled parameters, simplifying rules and discrete coordination modes emerge naturally. We present experimental results from a range of motor tasks to support this theory.

Feedback↗

PubMed2002

Sensorimotor adaptation of speech I: Compensation and adaptation.

When motor actions (e.g., reaching with your hand) adapt to altered sensory feedback (e.g., viewing a shifted image of your hand through a prism), the phenomenon is called sensorimotor adaptation (SA). In the study reported here, SA was observed in speech. In two 2-hour experiments (adaptation and control), participants whispered a variety of CVC words. For those words containing the vowel /E/, participants heard auditory feedback of their whispering. A DSP-based vocoder processed the participants' auditory feedback in real time, allowing the formant frequencies of participants' auditory speech feedback to be shifted. In the adaptation experiment, formants were shifted along one edge of the vowel triangle. For half the participants, formants were shifted so participants heard /a/ when they produced /E/; for the other half, the shift made participants hear /i/ when they produced /E/. During the adaptation experiment, participants altered their production of /E/ to compensate for the altered feedback, and these production changes were retained when participants whispered with auditory feedback blocked by masking noise. In a control experiment, in which the formants were not shifted, participants' production changes were small and inconsistent. Participants exhibited a range of adaptations in response to the altered feedback, with some participants adapting almost completely, and other participants showing very little or no adaptation.

Adaptation, Physiological↗