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What is the acceleration profile of a cheetah?

What is the acceleration profile of a cheetah?



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I'm interested in the time it takes for a cheetah to reach maximum velocity as well as the acceleration over time that's typical of a cheetah prior to attaining this peak velocity.


According to a recent paper published on Nature, cheetahs can reach a top speed of 29ms-1 and very impressive accelerations, up to 100ms-2:

The mean top speed was 14.9 +- 3.4ms-1 and was usually only sustained for 1-2 s. The highest speed we recorded was a stride-averaged 25.9-1

Also impressive are the lateral accelerations:

Hunts involved considerable manoeuvring, with maximum lateral (centripetal) accelerations often exceeding 13ms-2

Here is the acceleration and speed chart:

The paper has several other charts: Locomotion dynamics of hunting in wildcheetahs


How Fast Can a Cheetah Run?

The cheetah (Acinonyx jubatus) is the fastest land animal on Earth, capable of reaching speeds as high as 75 mph or 120 km/h. Cheetahs are predators that sneak up on their prey and sprint a short distance to chase and attack.

While a cheetah's top speed ranges from 65 to 75 mph (104 to 120 km/h), its average speed is only 40 mph (64 km/hr), punctuated by short bursts at its top speed. In addition to speed, a cheetah attains high acceleration. It can reach a speed of 47 mph (75 km/hr) in two seconds, or go from zero to 60 mph in 3 seconds and three strides. A cheetah accelerates as fast as one of the world's most powerful sports cars.

Key Takeaways: How Fast Can a Cheetah Run?

  • The top speed of a cheetah is around 69 to 75 mph. However, the cat can only sprint a short distance of around 0.28 miles. A cheetah is about 2.7 times faster than the fastest human runner.
  • A cheetah accelerates very quickly, allowing it to overtake prey at close range.
  • The fastest cheetah on record is Sarah. Sarah lives at the Cinncinati Zoo in Ohio. She ran the 100 meter dash in 5.95 seconds with a top speed of 61 mph.

Study of Muscle Fibres Reveal Cheetahs Speed Secrets

Just the word &lsquocheetah&rsquo is enough to evoke images of a sleek and nimble big cat blending easily into high, dry grasslands of the sub-Saharan Africa, silently stalking an antelope or a hare before sprinting at an incredible pace along the open grassy plains to bring down its unsuspecting prey.

With its sharp eyesight, stealthy movements and raw velocity, the cheetah is probably one of the world&rsquos most formidable hunters. What makes it one of the deadliest and most successful predators is its extraordinary speed and ability to take quick and sudden turns while in hot pursuit of its prey.

The cheetah is recognized as the world’s fastest land mammal. According to National Geographic.com, this elegant and graceful member of cat family can go from 0 to 60 miles (96 kilometers) an hour in only three seconds&hellip. an acceleration that would leave most of its competition in the dust.

Now a team of Japanese researchers has successfully mapped the muscle fibers of the cheetah to find the secret which enables this hunter to accelerate to record-breaking speeds within seconds. The findings have been published in the journal Mammalian Biology and examine how the muscle fibers of domestic cats and beagle dogs compare with those of the world’s fastest land mammal.

Dr Naomi Wada, the study’s co-author and Professor in System Physiology at Yamaguchi University in Japan has used the analogy of a &lsquorear wheel-drive car&rsquo to explain how the propulsive role of the hind limb is greater than the forelimb in the cheetah.

In a rear wheel drive car, the rear wheels of the automobile do the pushing while the front wheels are reserved for the steering duties. Other characteristics of rear wheel drive include better weight balance and better acceleration and de-acceleration on the road. Because of more effective distribution of balance, rear drive cars brake better and come to a stop more smoothly.

The cheetah&rsquos body is built for speed in a similar manner. The study finds that the functional difference between forelimb and hindlimb is the most remarkable in the cheetah as compared to the other animals under study. The different types of muscle fibers in a cheetah are also suited to different activities.

The researchers found that there is a high percentage of Type IIx fibers spread over a wide range from the thoracic to lumbar parts in a cheetah. Type IIx or “fast” fibers have low endurance but create a high force output and are key to fast running or galloping. Cheetah&rsquos muscle fibers also ensure that the mammal can produce a strong and quick extension of the spinal column and increase its stiffness during locomotion which is necessary for the rapid sprinting motion.

Due to its long, flexible limbs, a sprinting cheetah spends more than half its time airborne and controls its balance by using its forefeet to turn and slow down. A cheetah uses its exceptionally keen eyesight to scan its environment for any signs of prey. If spotted, the cheetah goes for the kill with the amazing speed and skill that Nature has endowed upon it. It would then drag its prey to a shady hiding place and enjoy its meal.


Breeding and Population

Female cheetahs typically have a litter of three cubs and live with them for one and a half to two years. Young cubs spend their first year learning from their mother and practicing hunting techniques with playful games. Male cheetahs live alone or in small groups, often with their littermates.

Most wild cheetahs are found in eastern and southwestern Africa. These populations are under pressure as the wide-open grasslands they favor are disappearing at the hands of human settlers.


How cheetahs outpace greyhounds

Cheetahs are the high-performance sports cars of the animal kingdom, but how do they outstrip other elite athletes when using the same sprint technique? Biologists compared the performance of captive cheetahs and greyhounds and found that in addition to increasing their stride frequency, the cheetahs spend longer in contact with the ground, probably to protect their limbs from stress fractures at high speed.

In a 0-60 mph stand off, most cars would be hard pressed to give a cheetah a run for its money, and at their highest recorded speed of 29m/s (65mph) cheetahs easily outstrip the fastest greyhounds. But, according to Alan Wilson from the Royal Veterinary College, UK, there is no clear reason for the cheetah's exceptional performance. 'Cheetahs and greyhounds are known to use a rotary gallop and physically they are remarkably similar, yet there is this bewitching difference in maximum speed of almost a factor of two', he says. Teaming up with Penny Hudson and Sandra Corr, Wilson decided to compare how cheetahs and greyhounds sprint to see if there were any mechanical differences between the two animals' movements.

Knowing that captive big cats are happy to chase a lure, the trio were confident that they could get the cheetahs at ZSL Whipsnade Zoo, UK, and the Ann van Dyk Cheetah Centre, South Africa, to sprint across force plates buried in a track in the animals' enclosure. The problem would be getting the valuable equipment to work in the open. 'Force plates are cosseted, loved pieces of equipment that people don't generally take outside of the lab and bury in the ground in the English summer', Wilson chuckles. However, after successfully installing eight force plates in the cheetahs' enclosure, along with four high speed cameras filming at 1000frames/s, Hudson tempted the cheetahs to gallop along the track with a piece of chicken attached to a truck starter motor while she measured the forces exerted on the animals' limbs, their body motion and footfall patterns. She also repeated the measurements on galloping greyhounds back in the lab, filming the animals at a slower 350frames/s.

But, when Hudson compared the animals' top speeds, she was surprised to see that the trained greyhounds galloped faster than captive cheetahs, clocking up a top speed of 19m/s compared with the cheetahs' 17.8m/s. Nevertheless, Hudson was able to identify clear differences in the animals' stride patterns that could explain how wild cheetahs would outpace the dogs.

When running at the same speed, the big cats' stride was slightly longer than the greyhounds', although the cheetahs compensated for this with a slightly lower stride frequency. Also, the cheetahs increased their stride frequency as they shifted up through the gears -- running at 2.4strides/s at a leisurely 9m/s, rising to 3.2strides/s at their top speed of 17m/s -- whereas the greyhounds maintained a constant stride rate around 3.5strides/s across their entire speed range. Wilson suspects that wild cats may be able to reach stride frequencies of 4strides/s, which, in combination with longer stride lengths, may allow them to outstrip their captive cousins and hit top speeds of 29m/s.

Also, when Hudson analysed the length of time that each animal's foot remained in contact with the ground -- the stance time -- she noticed that for some of the cheetah's limbs it was longer, and the team suspects that this may be another factor that contributes to the wild cheetah's record performance. Explaining that increasing the stance time reduces the peak loads on the animal's legs, Wilson says, '[with] a longer stance time the cheetah will get to the limiting load at higher speed than the greyhound'.

Speculating about the relatively poor performance of the captive cheetahs, Wilson suggests that they may lack motivation. 'They have lived in a zoo for several generations and have never had to run to catch food. They have probably never learned to run particularly', he says, adding, 'The next stage is to try to make measurements in wild cheetahs in the hope of seeing higher speeds.'


Some not amazing cheetah facts

Once found throughout Asia and Africa, today Cheetah is IUCN Red Listed as vulnerable, as it suffered a substantial decline in its historic range in the 20th century due to habitat loss, poaching, illegal pet trade, and conflict with humans .

By 2016, the global cheetah population has been estimated at approximately 7,100 individuals in the wild. making the cheetah Africa’s most endangered big cat. This number has dropped from 100,000 a century ago.

Most wild cheetahs exist in fragmented populations in pockets of Africa, occupying a mere 9% of their historic range. In Iran, less than 50 Asiatic cheetahs (a sub-species) remain.

More than 75 percent of cheetahs in Africa live outside protected areas and on lands shared with rural farming communities. This causes conflicts with humans – which is really bad for the big cat.

Also, adult life for a cheetah is difficult. Cheetahs live fast and die young. There is competition between territorial males, which often results in death. The lifespan of an adult male is only 8 years.

They have a lot of enemies in the wild including lions, leopards, African wild dogs, and hyenas.

Adult mortality is one of the most significant limiting factors for cheetah population growth and survival.


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Cheetah vs. Greyhound: Which One Is Faster?

With Cheetahs going from 0 to 60 mph in around three seconds, they can easily outpace last year´s Ford Mustang, but just what propels the world´s quickest land animal to record rates?

That´s what a team of UK and South African researchers set out to find out in comparing them to greyhounds, according to their report in the latest edition of The Journal of Experimental Biology.

“Cheetahs and greyhounds are known to use a rotary gallop and physically they are remarkably similar, yet there is this bewitching difference in maximum speed of almost a factor of two,” said study co-author Alan Wilson from the Royal Veterinary College of London, in a statement.

To compare the two animals, the researchers first enticed the big cats living in the ZSL Whipsnade Zoo, UK, and the Ann van Dyk Cheetah Centre, South Africa to run after bait and across force plates buried in the ground while filming the chase at 1,000 frames per second.

“Force plates are cosseted, loved pieces of equipment that people don’t generally take outside of the lab and bury in the ground in the English summer,” Wilson mused.

After taking measurements of the captive big cats´ stride, footfall patterns, and force exertions–they shifted the same test procedure over to their greyhound subjects. The only exception being that the speedy dogs were filmed at a leisurely 350 frames per second.

In watching video of the two animals´ stride patterns, the team initially found that the cheetahs´ strides were slightly longer with a slightly lower frequency. However, as they shift into upper gears, the fast and furious felines increase frequency from 2.4 strides per second at 20 mph up to 3.2 strides per second at their top speed of 40 mph. In contrast, the dogs stayed at around 3.5 strides per second throughout their range.

Surprisingly, the dogs´ maximum speed was faster than the cats´ at 42.5 mph. In the wild, Wilson said cheetahs may likely reach 4 strides per second, which could explain their greater top speeds measured at around 65 mph.

The researchers also analyzed the length of time that each animal’s foot remained in contact with the ground — known as the stance time. For some of the cheetah’s limbs it was longer than the greyhounds, and the team suspects that this may be another factor that contributes to the wild cheetah’s record performance. Wilson explained that by increasing the stance time, the animal put less strain on the animals legs and “'[with] a longer stance time the cheetah will get to the limiting load at higher speed than the greyhound.”

The captive cats most likely failed to run anywhere near record speeds because they lack motivation or have unusually sedentary lifestyle. Wilson expects to solve this problem in his future research.

“They have lived in a zoo for several generations and have never had to run to catch food,” he said. “The next stage is to try to make measurements in wild cheetahs in the hope of seeing higher speeds.”


The cheetah and racing greyhound are of a similar size and gross morphology and yet the cheetah is able to achieve a far higher top speed. We compared the kinematics and kinetics of galloping in the cheetah and greyhound to investigate how the cheetah can attain such remarkable maximum speeds. This also presented an opportunity to investigate some of the potential limits to maximum running speed in quadrupeds, which remain poorly understood. By combining force plate and high speed video data of galloping cheetahs and greyhounds, we show how the cheetah uses a lower stride frequency/longer stride length than the greyhound at any given speed. In some trials, the cheetahs used swing times as low as those of the greyhounds (0.2 s) so the cheetah has scope to use higher stride frequencies (up to 4.0 Hz), which may contribute to it having a higher top speed that the greyhound. Weight distribution between the animal's limbs varied with increasing speed. At high speed, the hindlimbs support the majority of the animal's body weight, with the cheetah supporting 70% of its body weight on its hindlimbs at 18 m s –1 however, the greyhound hindlimbs support just 62% of its body weight. Supporting a greater proportion of body weight on a particular limb is likely to reduce the risk of slipping during propulsive efforts. Our results demonstrate several features of galloping and highlight differences between the cheetah and greyhound that may account for the cheetah's faster maximum speeds.

The galloping cheetah [Acinonyx jubatus (Schreber 1775)] is characterised by the extreme movements of its back, and its rapidly swinging limbs, but primarily for its remarkable top speed. The fastest recorded speed of a cheetah is 29 m s –1 as an average over a 200 m course (Sharp, 1997), and thus its top speed is likely to be even greater. In contrast, the fastest canid, the racing greyhound (Canis familiaris L.), has a top speed of just 17 m s –1 (Jayes and Alexander, 1982 Usherwood and Wilson, 2005), despite the two animals being of a similar mass and gross morphology. Anatomical studies (Hudson et al., 2011a Hudson et al., 2011b) have presented no clear reason as to why there is such a large difference in their top speeds, and there is no clear consensus in the literature as to what fundamentally limits the maximum running speed of a quadruped. Here, we studied the kinematics and kinetics of galloping in the cheetah and racing greyhound to investigate how the cheetah attains faster speeds than the greyhound, and to explore some of the theorised limits to maximum running speed.

The determinants of maximum running speed have been examined in detail for humans, and three major limits have been proposed peak limb force, minimum achievable swing time and muscular power however, such limits in quadrupeds remain relatively unexplored. During a stride an animal must produce a vertical impulse that is equal to the product of its body weight and stride time in order to support its body weight. The impulses required to do this must be generated during stance, and therefore, because of decreases in contact time and duty factor with increasing speed (observed in several animals) (Hoyt and Taylor, 1981 Kram and Taylor, 1990 Usherwood and Wilson, 2005 Weyand et al., 2000 Witte et al., 2006), greater peak ground reaction forces (GRFs) must be resisted by the limbs to support the body weight of the animal. An animal may therefore encounter a speed where its limbs cannot resist a higher peak GRF (a force limit) perhaps due to the contraction properties or architecture of its muscles, or the safety limits of the skeletal elements of the limb may be approached. The animal can therefore increase its speed no further, and should slow down to increase contact time and reduce peak force. This phenomenon appears to be true for humans, as they run slower with longer contact times when going round a bend a situation that simulates an increase in body weight as a result of the centripetal forces experienced by the runner (Bowtell et al., 2007 Usherwood and Wilson, 2006). This allows them to maintain constant peak limb forces, suggesting that they have already reached a peak limb force limit when running on the straight. In a similar study on racing greyhounds, it became apparent that, unlike humans, greyhounds are not constrained by the peak GRFs experienced during maximal speed running (Usherwood and Wilson, 2005). Despite this, the maximum speed of a turning racehorse appears to be limited by peak limb force and thus whether this is a constraint that is universal for all quadrupeds remains unknown (Tan and Wilson, 2010). All of these studies, however, relied on estimates of peak GRF from duty factor, estimates of body weight distribution (Jayes and Alexander, 1978), and an assumption that the GRF is sinusoidal thus, the peak force estimates could be somewhat incorrect.

Another proposed limit to speed is the minimum time in which an animal can reposition its limb during swing. There are several adaptations that can minimise the muscular work required to swing the limb, some of which have been observed in both the cheetah and greyhound. Reduced distal limb mass is observed in both species and will reduce the inertia of the limb (Hudson et al., 2011a Hudson et al., 2011b Williams et al., 2008a Williams et al., 2008b). Muscle insertions that are close to the joint will allow faster joint rotational velocities for a given change in muscle length and are observed in the greyhound, but the cheetah hip and shoulder muscles tend to have long moment arms by comparison (Hudson et al., 2011a Hudson et al., 2011b). Finally, the recruitment of fast glycolytic or long muscle fibres that will contract at higher velocities than slow oxidative or short fibres will rotate the limb more rapidly. Fast fibres have been shown to be prevalent in cheetahs (Hyatt et al., 2010 Williams et al., 1997), and in the greyhound when compared with other dog breeds (Rodriguez-Barbudo et al., 1984). Weyand highlighted the importance of this limit in humans, illustrating there to be no variation in the minimum limb swing times (0.37 s) achieved by elite athletes and non-runners (Weyand, 2000). In horses, protraction of the limb is believed to be a rapid catapult process (Lichtwark et al., 2009 Wilson et al., 2003), as there is no significant variation in swing time (0.35 s) with increasing speed in the horse (Witte et al., 2006). To achieve high speeds, an ability to minimise swing times is crucial.

The final limit is the muscular power that an animal has to replace losses in centre of mass (CoM) energy during a stride. An animal may reach a speed at which the power requirements to maintain a constant horizontal speed are so great that it is unable to accelerate further. This limit has been studied by increasing the power requirements on an individual through incline running. In humans, the cost of locomotion has been shown to increase with increased gradient. This results in a decrease in running speed (Minetti et al., 1994) however, such studies were performed at sub-maximal speeds and thus as a limit to maximal speed, muscular power remains relatively unexplored.

There is minimal information on the stride parameters used by the cheetah. One study reported that at 25 m s –1 a cheetah completes a stride in 0.28 s with a stride length of 7 m, but no other temporal information or any GRF information is known (Hildebrand, 1961). Two studies have investigated limb forces during galloping in dogs (Bryant et al., 1987 Walter and Carrier, 2007), but none have examined steady-state galloping in the greyhound, which has a highly specialised morphology compared with other canids (Williams et al., 2008a Williams et al., 2008b).

Subject information and the number of strides and single limb contacts (SLCs) analysed for each individual


What Give Cheetahs The Edge In a Race With Greyhounds

A cheetah in full stride (courtesy of flickr user ShootNFish)

If you could put a wild cheetah up against a greyhound in a race, the cheetah would win, no problem. After all, the cheetah’s top recorded speed is 65 mph, and the cats are thought to be capable of much more. Greyhounds top out around 40 mph, fast enough to provide a show for bettors at the racetrack, but no match for the cats.

But why should that be? Cheetahs and greyhounds are about the same size, and they’ve got similar body shapes. In a new study in the Journal of Experimental Biology, biologists from the University of London made a series of measurements of cheetahs from a zoo in England and a cheetah center in South Africa and greyhounds that had retired from their racing careers in England to figure out why the cats are faster. The animals were filmed with high-speed cameras as they raced along a 100-yard track chasing a mechanical lure. Some of them were also trained to run across a force plate.

The cats and dogs had several differences in how they ran–at any given speed, the cheetahs used longer strides and fewer of them than the greyhounds. The cats also supported their weight differently, putting more of it on their hindlimbs, which may enhance their grip and allow for better acceleration and maneuvering while leaving their forelimbs free to capture prey.

But the scientists can’t say definitively that they’ve found out why cheetahs are faster because these cheetahs weren’t. They topped out at 39.8 mph, never reaching anywhere close to 65 mph and not even running faster than the greyhounds in the study. “They have lived in a zoo for several generations and have never had to run to catch food. They have probably never learned to run particularly,” says Alan Wilson, one of the project scientists. The greyhounds, meanwhile, were trained for races, encouraged to develop to run at the fastest speeds possible.

Io9 called this a failed experiment, since the captive cheetahs were so slow. But I would argue otherwise–the researchers identified plenty of differences between the two animals that may explain the cheetah’s edge, which was the point of the study. That said, it would be nice if they could try this with with wild cheetahs, which Wilson says they will try. Though I suspect that wrangling one of those speedy cats will provide new challenges to the researchers.


Accelerated Profile HMM Searches

Profile hidden Markov models (profile HMMs) and probabilistic inference methods have made important contributions to the theory of sequence database homology search. However, practical use of profile HMM methods has been hindered by the computational expense of existing software implementations. Here I describe an acceleration heuristic for profile HMMs, the "multiple segment Viterbi" (MSV) algorithm. The MSV algorithm computes an optimal sum of multiple ungapped local alignment segments using a striped vector-parallel approach previously described for fast Smith/Waterman alignment. MSV scores follow the same statistical distribution as gapped optimal local alignment scores, allowing rapid evaluation of significance of an MSV score and thus facilitating its use as a heuristic filter. I also describe a 20-fold acceleration of the standard profile HMM Forward/Backward algorithms using a method I call "sparse rescaling". These methods are assembled in a pipeline in which high-scoring MSV hits are passed on for reanalysis with the full HMM Forward/Backward algorithm. This accelerated pipeline is implemented in the freely available HMMER3 software package. Performance benchmarks show that the use of the heuristic MSV filter sacrifices negligible sensitivity compared to unaccelerated profile HMM searches. HMMER3 is substantially more sensitive and 100- to 1000-fold faster than HMMER2. HMMER3 is now about as fast as BLAST for protein searches.

Conflict of interest statement

The author has declared that no competing interests exist.

Figures

A: Profile HMM architecture used by HMMER3 , , .…

A: Profile HMM architecture used by HMMER3 , , . Regions homologously aligned to the query are represented by a linear core model consisting of consensus positions (in this example, ), each consisting of a match, a delete, and an insert state (shown as boxes marked M, circles marked D, and diamonds marked I), connected by state transition probabilities (arrows). Match states carry position-specific emission probabilities for scoring residues at each consensus position. Insert states emit residues with emission probabilities identical to a background distribution. Additional flanking states (marked N, C, and J) emit zero or more residues from the background distribution, modeling nonhomologous regions preceding, following, or joining homologous regions aligned to the core model. Start (S), begin (B), end (E) and termination (T) states do not emit. B: The MSV profile is formed by implicitly treating all match-match transition probabilities as 1.0. This corresponds to the virtual removal of the delete and insert states. The rest of the profile parameterization stays the same. This model generates sequences containing one or more ungapped local alignment segments. Note that both models appear to be improperly normalized for example, each match state in the MSV model has probability 1.0 local exit transition (orange arrows) in addition to the probability 1.0 match-match transition. This is because of a trick used to establish a uniform local fragment length distribution, in which these profiles are collapsed representations of a much larger (and properly normalized) “implicit probability model”, as explained in . C: An example of what an alignment of a larger MSV profile (of length ) to a target sequence (of length ) might look like, as a path through a dynamic programming (DP) matrix. Here, the model identifies two high-scoring ungapped alignment segments (black dots, indicating residues aligned to profile match states), and assigns all other residues to N, J, and C states in the model (orange dots unfilled indicates a “mute” nonemitting state or state transition). Note that the ungapped diagonals are not enforced to be consistent with a single gapped alignment.

Figure 2. Illustration of striped indexing for…

Figure 2. Illustration of striped indexing for SIMD vector calculations.

The top row (magenta outline)…

The top row (magenta outline) shows one row of the dynamic programming lattice for a model of length . Assuming an example of vectors containing cells each, the 14 cells are contained in vectors numbered . (Two unused cells, marked x, are set to a sentinel value.) In the dynamic programming recursion, when we calculate each new cell in a new row , we access the value in cell in the previous row . With striped indexing, vector contains exactly the four cells needed to calculate the four cells in a new vector on a new row of the dynamic programming matrix (turquoise outline). For example, when we calculate cells in vector , we access the previous row's vector which contains the cells we need in the order we need them, (dashed lines and box). If instead we indexed cells into vectors in the obvious way, in linear order ( in vector and so on), there is no such correspondence of with four 's, and each calculation of a new vector would require expensive meddling with the order of cells in the previous row's vectors. With striped indexing, only one shift operation is needed per row, outside the innermost loop: the last vector on each finished row is rightshifted (mpv, in grey with red cell indices) and used to initialize the next row calculation.

Figure 3. MSV scores follow a predictable…

Figure 3. MSV scores follow a predictable distribution.

A: example MSV score distributions for a…

A: example MSV score distributions for a typical Pfam model, CNP1, on random i.i.d. sequences of varying lengths from 25 to 25,600, with the shortest, typical, and longest lengths highlighted as red, black, and blue lines, respectively. The predicted distribution, following the procedure of including an edge correction on the slope , is shown in orange (though largely obscured by the data lines right on top of it). B: Histogram of maximum likelihood values obtained from score distributions of 11,912 Pfam models, showing that most are tolerably close to the conjectured , albeit with more dispersion for default entropy-weighted models (black line) than high relative entropy models without entropy-weighting (gray line). C: The observed fraction of nonhomologous sequences that pass the filter at a P-value of 0.02 should be 0.02. Histograms of the actual filter fraction for 11,912 different Pfam 24 models are shown, for a range of random sequence lengths from 25 to 25,600, for both default models (black lines) and high relative entropy models with no entropy weighting (gray lines).

Figure 4. The HMMER3 acceleration pipeline.

Figure 4. The HMMER3 acceleration pipeline.

Representative calculation speeds are shown in red, in units…

Figure 5. Speed benchmarks.

Figure 5. Speed benchmarks.

Each point represents a speed measurement for one search with one…

Each point represents a speed measurement for one search with one query against target sequences ( for the slow HMMER2 and SAM programs, for FASTA and SSEARCH), on a single CPU core (see Methods for more details). Both axes are logarithmic, for speed in millions of dynamic programming cells per second (Mc/s) on the y-axis and query length in residues on the x-axis. Panel A shows “typical best performance” speed measurements for several different programs including HMMER3, for 76 queries of varying consensus lengths, chosen from Pfam 24, for searches of randomized (shuffled) target sequences. Panel B shows a wider range of more realistic speed measurements for all 11,912 profiles in Pfam 24, on searches of real target protein sequences from UniProt TrEMBL.


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