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PubMed2000

Optimization of dairy heifer management decisions based on production conditions of Pennsylvania.

We used a dynamic programming model to determine optimum rearing decisions of dairy replacements. Heifers were described in the model by age, season, body weight, pregnancy state, and prepubertal growth rate. Prices and parameters were chosen to represent the dairy population of Pennsylvania. We calculated monthly costs and revenues from calf value, feed costs, veterinary costs, semen costs, carcass value, and full-grown heifer value. The model considered a stochastic variation in the onset of puberty, conception, involuntary disposal, and a seasonal variation in the prices of calves, heifers, and feed. Based on a critical prepubertal average daily gain of 0.9 kg/d and a maximum achievable postpubertal growth rate of 1.1 kg/d, the optimum practice resulted in an average age at first calving of 20.5 mo at a body weight of 563 kg. Discounted net returns equaled $107 per heifer per year. The optimum rearing practice was not sensitive to seasonal variation in prices. Nevertheless, the economic results per season of birth varied considerably; the highest income per heifer was obtained from heifers born in December ($142/yr), whereas those born in May yielded the lowest ($100/yr). Sensitivity analyses demonstrated a considerable influence of growth rate restrictions and variation in reproductive performance on both the optimal rearing practices as the expected net returns.

Animal Feed↗
PubMed1994

Optimal replacement of mastitic cows determined by a hierarchic Markov process.

Farmers frequently have to decide whether to keep or to replace cows that suffer from clinical mastitis. A dynamic programming model was developed to optimize these decisions for individual cows within the herd, using the hierarchic Markov process technique. This technique provides a method to model a wide variety of cows, differing in age, productive performance, reproductive status, and clinical mastitis occurrence. The model presented was able to support decisions related to 63% of all replacements. Results--for Dutch conditions--showed the considerable impact of mastitis on expected income of affected cows. Nevertheless, in most cases, the optimal decision was to keep and to treat rather than to replace the cow. Clinical mastitis occurring in the previous lactation negligibly influence expected income. Clinical mastitis in current lactation, especially in the current month, however, had a significant effect on expected income. Total losses caused by clinical mastitis were US$83/yr per cow. Farm level treatment, which reduced incidence by 25%, on a farm with 10 clinical quarter cases per 10,000 cow days, may cost at maximum US$27/yr per cow.

Animals↗
PubMed1994

Present and future uses of selection index methodology in dairy cattle.

Selection indexes have been extensively applied in the estimation of breeding value of dairy cattle for single traits as well as for combinations of traits for selection purposes. Milestones in methodology, such as multiple-trait evaluation procedures by BLUP, (co)variance component estimation, nonlinear models, discounted gene flow, dynamic programming, and international sire evaluations, together with increased computing power and the development of integrated AI and recording schemes, have contributed to efficient implementation of selection indexes and are reviewed in this article. Results of an international survey on evaluation practices and breeding programs are presented, demonstrating wide adoption of index selection for total merit and the need for further applications. Results from a simulation study on the efficiency of index selection for total merit are also presented; when the breeding goal includes, in addition to production traits, functional nonproduction traits such as mastitis resistance and fertility, failure to consider these traits in the selection index decreases efficiency 15 to 25%. Future applications are also discussed in view of advances in the areas of genome mapping, marker detection, and international comparisons. Further research should focus on functional nonproduction traits.

Animal Husbandry↗
PubMed1999

Optimal replacement and insemination policies for Holstein cattle in the southeastern region of Brazil: the effect of selling animals for production.

Dynamic programming was used to determine optimal replacement and insemination policies for Holstein-Friesian cattle in the southeastern region of Brazil. Optimal insemination and replacement decisions were determined for two disposal alternatives: selling all cows exclusively for slaughter (A) or selling the cows either for slaughter or to other farmers for production (B). Disposal alternative B reflects the common practice among dairy farmers to sell some of their cows to other farmers at a higher price than the carcass price. In the model, cows were described in terms of lactation number, stage of lactation, calving interval, and milk produced during present and previous lactation. For disposal alternative A, the optimal average herd life was 54.9 mo, corresponding to annual replacement and voluntary culling rates of 21.8 and 4.1%, respectively. For disposal alternative B, the optimal average herd life was 44.0 mo, which corresponded to annual replacement and voluntary culling rates of 27.3 and 10.0%, respectively. In this case, from the total of voluntarily culled cows, 70% were sold to other farmers for production. Sensitivity analyses showed that changes in the disposal value of cows and replacement heifer prices strongly influenced the optimal insemination and replacement policy.

Abattoirs↗
PubMed1999

Analysis of ribosomal RNA sequences by combinatorial clustering.

We present an analysis of multi-aligned eukaryotic and procaryotic small subunit rRNA sequences using a novel segmentation and clustering procedure capable of extracting subsets of sequences that share common sequence features. This procedure consists of: i) segmentation of aligned sequences using a dynamic programming procedure, and subsequent identification of likely conserved segments; ii) for each putative conserved segment, extraction of a locall homogeneous cluster using a novel polynomial procedure; and iii) intersection of clusters associated with each conserved segment. Aside from their utilit in processing large gap-filled multi-alignments, these algorithms can be applied to a broad spectrum of rRNA analysis functions such as subalignment, phylogenetic subtree extraction and construction, and organism tree-placement, and can serve as a framework to organize sequence data in an efficient and easily searchable manner. The sequence classification we obtained using the method presented here shows a remarkable consistency with the independently constructed eukaryotic phylogenetic tree.

Algorithms↗
PubMed2000

Key residues approach to the definition of protein families and analysis of sparse family signatures.

We extend the concept of the motif as a tool for characterizing protein families and explore the feasibility of a sparse "motif" that is the length of the protein sequence itself. The type of motif discussed is a sparse family signature consisting of a set of N key residue positions (A1, A2...AN) preceded by gaps (G) thus G1A1G2A2. ...GNAN. Both a residue and gap can be variable. A signature is matched to a protein sequence and scored using a dynamic programming algorithm which permits variability in gap distance and residue type. Generating a signature involves identifying residues associated with points of contact in interactions between secondary structure elements. A raw signature consists of a set of positions with potential key structural roles sampled from a sequence alignment constructed with reference to this contact data. Raw signatures are refined by sampling different gap-residue pairs until the specificity of a signature for the family cannot be further improved. We summarize signatures for nine families of protein of diverse fold and function and present results of scans against the OWL protein sequence database. The implications of such signatures are discussed.

Algorithms↗
PubMed2000

Optimizing breeding decisions for Finnish dairy herds.

The purpose of this study was to determine the effect of reproductive performance on profitability and optimal breeding decisions for Finnish dairy herds. We used a dynamic programming model to optimize dairy cow insemination and replacement decisions. This optimization model maximizes the expected net revenues from a given cow and her replacements over a decision horizon. Input values and prices reflecting the situation in 1998 in Finland were used in the study. Reproductive performance was reflected in the model by overall pregnancy rate, which was a function of heat detection and conception rate. Seasonality was included in conception rate. The base run had a pregnancy rate of 0.49 (both heat detection and conception rate of 0.7). Different scenarios were modeled by changing levels of conception rate, heat detection, and seasonality in fertility. Reproductive performance had a considerable impact on profitability of a herd; good heat detection and conception rates provided an opportunity for management control. When heat detection rate decreased from 0.7 to 0.5, and everything else was held constant, net revenues decreased approximately 2.6%. If the conception rate also decreased to 0.5 (resulting in a pregnancy rate of 0.25), net revenues were approximately 5% lower than with a pregnancy rate of 0.49. With lower fertility, replacement percentage was higher and the financial losses were mainly from higher replacement costs. Under Finnish conditions, it is not optimal to start breeding cows calving in spring and early summer immediately after the voluntary waiting period. Instead, it is preferable to allow the calving interval to lengthen for these cows so that their next calving is in the fall. However, cows calving in the fall should be bred immediately after the voluntary waiting period. Across all scenarios, optimal solutions predicted most calvings should occur in fall and the most profitable time to bring a replacement heifer into a herd was in the fall. It was economically justifiable to keep breeding high producing cows longer than low producing cows.

Animal Husbandry↗
PubMed2000

A probabilistic learning approach to whole-genome operon prediction.

We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this task from a rich variety of data types including sequence data, gene expression data, and functional annotations associated with genes. We use multiple learned models that individually predict promoters, terminators and operons themselves. A key part of our approach is a dynamic programming method that uses our predictions to map every known and putative gene in a given genome into its most probable operon. We evaluate our approach using data from the E. coli K-12 genome.

Gene Expression Profiling↗
PubMedDate not supplied

[A rapid method of searching for homology of nucleic acid sequences].

A new method of the homology search between DNA sequences was suggested. This method may be used to find extensive and not strong homologies with point mutations and deletions. The computer time to compare sequences is less than dynamic program algorithms at least by four orders of magnitude. It makes possible to use the method for homology search all over the nucleotide bank by personal computers. Some results of homology search are presented.

Algorithms↗
PubMed1987

Induction of common patterns of polypeptide synthesis and phosphorylation by calcium and 12-O-tetradecanoylphorbol-13-acetate in mouse epidermal cell culture.

Terminal differentiation can be induced in cultured basal cells by either increasing the Ca2+ level in the medium from 0.05 to 1.4 mM or by exposure to the tumor promoter 12-O-tetradecanoylphorbol-13-acetate (TPA). If Ca2+ and TPA act by a common mechanism, then a common pattern of protein synthesis and/or phosphorylation would be expected. Computer-assisted analysis of radioactively labeled polypeptides separated by two-dimensional-polyacrylamide gel electrophoresis was utilized to study protein synthesis and phosphorylation. Within 1 h of increasing the Ca2+ level in the medium, the synthesis of 57 polypeptides was altered by 2-fold or more. Similarly, exposure to TPA for 1 h affected the synthesis of 106 polypeptides. Sixteen polypeptides were affected by both Ca2+ and TPA; the synthesis of nine was increased and seven was decreased, with changes in the same direction for both effectors. By 4 h, the synthesis of 32 polypeptides was similarly modulated by both Ca2+ and TPA. Only one polypeptide which was increased at 1 h was still elevated at 4 h. These results suggest that a common dynamic program of protein synthesis, likely to be related to terminal keratinocyte differentiation, is induced by both Ca2+ and TPA. Overall phosphorylation of epidermal proteins was increased after 30 min of TPA treatment, but was not increased by Ca2+ at this time. Keratin polypeptides were heavily phosphorylated in low Ca2+ medium, but the level or pattern of phosphorylation of these proteins was not altered by either Ca2+ or TPA. Although phosphorylation of a minor polypeptide (pI 5.1/Mr 45,000) was increased 2-3-fold by both Ca2+ and TPA, most of the specific protein phosphorylation changes induced in keratinocytes by Ca2+ and TPA appear to be unique. Thus, if protein phosphorylation is an early signal for epidermal differentiation by each effector, only a single apparent common substrate is involved and multiple kinases are activated. Alternatively, substrate specificity of a single kinase may be differentially altered by each effector.

Animals↗
PubMed1985

Redistribution of arterial blood flow in metastases-bearing livers after infusion of degradable starch microspheres.

Changes in intrahepatic arterial blood flow after intraarterial injection of degradable starch microspheres (DSM) were studied in four patients undergoing hepatic arterial chemotherapy. All four livers contained metastases, three from colorectal cancer and one from melanoma. Using a CT scanner with a dynamic program, 8 mm liver sections were studied in each patient before and after the DSM infusion (180(-6) in 3 min). Density plots were obtained from 12 tumoral and 12 parenchymal areas after 5 ml push arterial injections of nonionic contrast medium. The areas under the curves (ID) were calculated. The ID after DSM infusion was reduced by 94% in a single hyperdense colorectal metastasis and by a mean of c. 82% in ten parenchymal areas. By contrast, nine hypodense colorectal metastases showed an average ID decrease of c. 156%. The ID of two melanoma metastases was reduced after DSM (-48% and -68%), while the ID of two matched parenchymal areas showed an approximately similar degree of increase (+36% and +64%). Since ID after contrast injection can be assumed to be a function of blood volume, mutual changes of parenchymal and tumoral blood flow appear to take place in metastases-bearing liver after arterial infusion of DSM. This phenomenon may be of diagnostic and therapeutic value for intraarterial chemotherapy of liver tumors.

Antineoplastic Agents↗
PubMedDate not supplied

[Tasks in planning biological experiments].

The paper describes certain cases of using mathematical methods in the planning of biological experiments. The paper presents an algorithm of the distribution of the experimental data based on dynamic programming. The paper discusses an application of computer-aided calculations for the formation of homogeneous groups of experimental and control tests.

Animals↗
PubMed1993

A modular learning environment for protein modeling.

We propose in this paper a modular learning environment for protein modeling. In this system, the protein modeling problem is tackled in two successive phases. First, partial structural informations are determined via numerical learning techniques. Then, in the second phase, the multiple available informations are combined in pattern matching searches via dynamic programming. It is shown on real problems that various protein structure predictions can be improved in this way, such as secondary structure prediction, alignment of weakly homologous protein sequences or protein model evaluations.

Amino Acid Sequence↗
PubMed1993

Discovering sequence similarity by the algorithmic significance method.

The minimal-length encoding approach is applied to define concept of sequence similarity. A sequence is defined to be similar to another sequence or to a set of keywords if it can be encoded in a small number of bits by taking advantage of common subwords. Minimal-length encoding of a sequence is computed in linear time, using a data compression algorithm that is based on a dynamic programming strategy and the directed acyclic word graph data structure. No assumptions about common word ("k-tuple") length are made in advance, and common words of any length are considered. The newly proposed algorithmic significance method provides an exact upper bound on the probability that sequence similarity has occurred by chance, thus eliminating the need for any arbitrary choice of similarity thresholds. Preliminary experiments indicate that a small number of keywords can positively identify a DNA sequence, which is extremely relevant in the context of partial sequencing by hybridization.

Algorithms↗
PubMed1993

FLASH: a fast look-up algorithm for string homology.

A key issue in managing today's large amounts of genetic data is the availability of efficient, accurate, and selective techniques for detecting homologies (similarities) between newly discovered and already stored sequences. A common characteristic of today's most advanced algorithms, such as FASTA, BLAST, and BLAZE is the need to scan the contents of the entire database, in order to find one or more matches. This design decision results in either excessively long search times or, as is the case of BLAST, in a sharp trade-off between the achieved accuracy and the required amount of computation. The homology detection algorithm presented in this paper, on the other hand, is based on a probabilistic indexing framework. The algorithm requires minimal access to the database in order to determine matches. This minimal requirement is achieved by using the sequences of interest to generate a highly redundant number of very descriptive tuples; these tuples are subsequently used as indices in a table look-up paradigm. In addition to the description of the algorithm, theoretical and experimental results on the sensitivity and accuracy of the suggested approach are provided. The storage and computational requirements are described and the probability of correct matches and false alarms is derived. Sensitivity and accuracy are shown to be close to those of dynamic programming techniques. A prototype system has been implemented using the described ideas. It contains the full Swiss-Prot database rel 25 (10 MR) and the genome of E. Coli (2 MR). The system is currently being expanded to include the complete Genbank database.(ABSTRACT TRUNCATED AT 250 WORDS)

Algorithms↗
PubMed1994

High speed pattern matching in genetic data base with reconfigurable hardware.

Homology detection in large data bases is probably the most time consuming operation in molecular genetic computing systems. Moreover, the progresses made all around the world concerning the mapping and sequencing of the genome of Homo Sapiens and other species have increased the size of data bases exponentially. Therefore even the best workstation would not be able to reach the scanning speed required. In order to answer this need we propose an algorithm, A2R2, and its implementation on a massively parallel system. Basically, two kinds of algorithms are used to search in molecular genetic data bases. The first kind is based on dynamic programming and the second on word processing, A2R2 belongs to the second kind. The structure of the motif (pattern) searched by A2R2 can support those from FAST, BLAST and FLASH algorithms. After a short presentation of the reconfigurable hardware concept and technology used in our massively parallel accelerator we present the A2R2 implementation. This parallel implementation outperforms any kind of previously published genetic data base scanning hardware or algorithms. We report up to 25 million nucleotides per scanning seconds as our best results.

Algorithms↗
PubMed1994

An improved system for exon recognition and gene modeling in human DNA sequences.

A new version of the GRAIL system (Uberbacher and Mural, 1991; Mural et al., 1992; Uberbacher et al., 1993), called GRAIL II, has recently been developed (Xu et al., 1994). GRAIL II is a hybrid AI system that supports a number of DNA sequence analysis tools including protein-coding region recognition, PolyA site and transcription promoter recognition, gene model construction, translation to protein, and DNA/protein database searching capabilities. This paper presents the core of GRAIL II, the coding exon recognition and gene model construction algorithms. The exon recognition algorithm recognizes coding exons by combining coding feature analysis and edge signal (acceptor/donor/translation-start sites) detection. Unlike the original GRAIL system (Uberbacher and Mural, 1991; Mural et al., 1992), this algorithm uses variable-length windows tailored to each potential exon candidate, making its performance almost exon length-independent. In this algorithm, the recognition process is divided into four steps. Initially a large number of possible coding exon candidates are generated. Then a rule-based prescreening algorithm eliminates the majority of the improbable candidates. As the kernel of the recognition algorithm, three neural networks are trained to evaluate the remaining candidates. The outputs of the neural networks are then divided into clusters of candidates, corresponding to presumed exons. The algorithm makes its final prediction by picking the best canadidate from each cluster. The gene construction algorithm (Xu, Mural and Uberbacher, 1994) uses a dynamic programming approach to build gene models by using as input the clusters predicted by the exon recognition algorithm. Extensive testing has been done on these two algorithms.(ABSTRACT TRUNCATED AT 250 WORDS)

Algorithms↗
PubMed1995

Multiple alignment using hidden Markov models.

A simulated annealing method is described for training hidden Markov models and producing multiple sequence alignments from initially unaligned protein or DNA sequences. Simulated annealing in turn uses a dynamic programming algorithm for correctly sampling suboptimal multiple alignments according to their probability and a Boltzmann temperature factor. The quality of simulated annealing alignments is evaluated on structural alignments of ten different protein families, and compared to the performance of other HMM training methods and the ClustalW program. Simulated annealing is better able to find near-global optima in the multiple alignment probability landscape than the other tested HMM training methods. Neither ClustalW nor simulated annealing produce consistently better alignments compared to each other. Examination of the specific cases in which ClustalW outperforms simulated annealing, and vice versa, provides insight into the strengths and weaknesses of current hidden Markov model approaches.

Algorithms↗